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Curso E-investigacioacuten bibliograacutefica
Ciencias Bioloacutegicas y Biomeacutedicas
Layla Michaacuten
Departamento de Biologiacutea Evolutiva
Facultad de Ciencias UNAM
Sesioacuten
Martes 22 Jueves 24
febrero de 2011
E-ciencia
Ciberinfraestructura
E-investigacioacuten
Grids
Transformacioacuten de la praacutectica cientiacutefica
ndash Social
ndash Infraestructura
ndash Fondos
ndash Colaboracioacuten
ndash Comunicacioacuten
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office
of Science and
Technology in 1999
bull Will refer to the large
scale science that will
increasingly be carried
out through distributed
global collaborations
enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la
Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero
de investigadores (en algunos casos cientos)
localizados en diversas regiones y con diferentes
especialidades que se forman grupos trabajo (Hey
y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones
452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)
bull European Molecular Biology Laboratory (EMBL) de datos de Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)
bull DNA Data Bank de Japoacuten (DDBJ)
bull Reciben las secuencias producidas en laboratorios de todo el mundo de maacutes de 100000 organismos distintos
bull Crece a un ritmo exponencial duplicando cada 10 meses Suelte 134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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1945
1950
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1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
Nature 2001 Feb 15409(6822)860-921
Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHughW Funke R Gage D Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernanK Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovic N Subramanian A Wyman D Rogers J Sulston J AinscoughR Beck S Bentley D Burton J Clee C Carter N Coulson A Deadman R Deloukas P Dunham ADunhamI Durbin R French L Grafham D Gregory S Hubbard T Humphray S Hunt A Jones M Lloyd C McMurrayA Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R SimsS Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER Fulton LA ChinwallaAT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenningS Slezak T Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA MuznyDM Scherer SE Bouck JB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML NaylorSL Kucherlapati RS Nelson DL Weinstock GM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A ItohT Kawagoe C Watanabe H Totoki YTaylor T Weissenbach J Heilig R Saurin W Artiguenave F BrottierP Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-Stamm L Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H Yu J Wang J HuangG Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K Minoshima S Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J LehrachH Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G AgarwalaR Aravind LBailey JA Bateman A Batzoglou S Birney E Bork P Brown DG Burge CB Cerutti L ChenHC Church D Clamp M Copley RR Doerks T Eddy SR Eichler EE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA KasifS Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF StupkaESzustakowski J Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ Osoegawa K Shizuya H Choi S Chen YJ International Human GenomeSequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
E-ciencia
Ciberinfraestructura
E-investigacioacuten
Grids
Transformacioacuten de la praacutectica cientiacutefica
ndash Social
ndash Infraestructura
ndash Fondos
ndash Colaboracioacuten
ndash Comunicacioacuten
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office
of Science and
Technology in 1999
bull Will refer to the large
scale science that will
increasingly be carried
out through distributed
global collaborations
enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la
Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero
de investigadores (en algunos casos cientos)
localizados en diversas regiones y con diferentes
especialidades que se forman grupos trabajo (Hey
y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones
452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)
bull European Molecular Biology Laboratory (EMBL) de datos de Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)
bull DNA Data Bank de Japoacuten (DDBJ)
bull Reciben las secuencias producidas en laboratorios de todo el mundo de maacutes de 100000 organismos distintos
bull Crece a un ritmo exponencial duplicando cada 10 meses Suelte 134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
0
100000
200000
300000
400000
500000
600000
700000
800000
1865
1870
1875
1880
1885
1890
1895
1900
1905
1910
1915
1920
1925
1930
1935
1940
1945
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
Nature 2001 Feb 15409(6822)860-921
Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHughW Funke R Gage D Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernanK Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovic N Subramanian A Wyman D Rogers J Sulston J AinscoughR Beck S Bentley D Burton J Clee C Carter N Coulson A Deadman R Deloukas P Dunham ADunhamI Durbin R French L Grafham D Gregory S Hubbard T Humphray S Hunt A Jones M Lloyd C McMurrayA Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R SimsS Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER Fulton LA ChinwallaAT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenningS Slezak T Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA MuznyDM Scherer SE Bouck JB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML NaylorSL Kucherlapati RS Nelson DL Weinstock GM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A ItohT Kawagoe C Watanabe H Totoki YTaylor T Weissenbach J Heilig R Saurin W Artiguenave F BrottierP Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-Stamm L Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H Yu J Wang J HuangG Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K Minoshima S Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J LehrachH Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G AgarwalaR Aravind LBailey JA Bateman A Batzoglou S Birney E Bork P Brown DG Burge CB Cerutti L ChenHC Church D Clamp M Copley RR Doerks T Eddy SR Eichler EE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA KasifS Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF StupkaESzustakowski J Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ Osoegawa K Shizuya H Choi S Chen YJ International Human GenomeSequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office
of Science and
Technology in 1999
bull Will refer to the large
scale science that will
increasingly be carried
out through distributed
global collaborations
enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la
Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero
de investigadores (en algunos casos cientos)
localizados en diversas regiones y con diferentes
especialidades que se forman grupos trabajo (Hey
y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones
452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)
bull European Molecular Biology Laboratory (EMBL) de datos de Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)
bull DNA Data Bank de Japoacuten (DDBJ)
bull Reciben las secuencias producidas en laboratorios de todo el mundo de maacutes de 100000 organismos distintos
bull Crece a un ritmo exponencial duplicando cada 10 meses Suelte 134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
Nature 2001 Feb 15409(6822)860-921
Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHughW Funke R Gage D Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernanK Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovic N Subramanian A Wyman D Rogers J Sulston J AinscoughR Beck S Bentley D Burton J Clee C Carter N Coulson A Deadman R Deloukas P Dunham ADunhamI Durbin R French L Grafham D Gregory S Hubbard T Humphray S Hunt A Jones M Lloyd C McMurrayA Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R SimsS Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER Fulton LA ChinwallaAT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenningS Slezak T Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA MuznyDM Scherer SE Bouck JB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML NaylorSL Kucherlapati RS Nelson DL Weinstock GM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A ItohT Kawagoe C Watanabe H Totoki YTaylor T Weissenbach J Heilig R Saurin W Artiguenave F BrottierP Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-Stamm L Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H Yu J Wang J HuangG Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K Minoshima S Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J LehrachH Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G AgarwalaR Aravind LBailey JA Bateman A Batzoglou S Birney E Bork P Brown DG Burge CB Cerutti L ChenHC Church D Clamp M Copley RR Doerks T Eddy SR Eichler EE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA KasifS Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF StupkaESzustakowski J Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ Osoegawa K Shizuya H Choi S Chen YJ International Human GenomeSequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la
Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero
de investigadores (en algunos casos cientos)
localizados en diversas regiones y con diferentes
especialidades que se forman grupos trabajo (Hey
y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones
452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)
bull European Molecular Biology Laboratory (EMBL) de datos de Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)
bull DNA Data Bank de Japoacuten (DDBJ)
bull Reciben las secuencias producidas en laboratorios de todo el mundo de maacutes de 100000 organismos distintos
bull Crece a un ritmo exponencial duplicando cada 10 meses Suelte 134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
Nature 2001 Feb 15409(6822)860-921
Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHughW Funke R Gage D Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernanK Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovic N Subramanian A Wyman D Rogers J Sulston J AinscoughR Beck S Bentley D Burton J Clee C Carter N Coulson A Deadman R Deloukas P Dunham ADunhamI Durbin R French L Grafham D Gregory S Hubbard T Humphray S Hunt A Jones M Lloyd C McMurrayA Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R SimsS Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER Fulton LA ChinwallaAT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenningS Slezak T Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA MuznyDM Scherer SE Bouck JB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML NaylorSL Kucherlapati RS Nelson DL Weinstock GM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A ItohT Kawagoe C Watanabe H Totoki YTaylor T Weissenbach J Heilig R Saurin W Artiguenave F BrottierP Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-Stamm L Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H Yu J Wang J HuangG Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K Minoshima S Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J LehrachH Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G AgarwalaR Aravind LBailey JA Bateman A Batzoglou S Birney E Bork P Brown DG Burge CB Cerutti L ChenHC Church D Clamp M Copley RR Doerks T Eddy SR Eichler EE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA KasifS Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF StupkaESzustakowski J Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ Osoegawa K Shizuya H Choi S Chen YJ International Human GenomeSequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la
Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero
de investigadores (en algunos casos cientos)
localizados en diversas regiones y con diferentes
especialidades que se forman grupos trabajo (Hey
y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones
452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)
bull European Molecular Biology Laboratory (EMBL) de datos de Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)
bull DNA Data Bank de Japoacuten (DDBJ)
bull Reciben las secuencias producidas en laboratorios de todo el mundo de maacutes de 100000 organismos distintos
bull Crece a un ritmo exponencial duplicando cada 10 meses Suelte 134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
0
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800000
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1890
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1910
1915
1920
1925
1930
1935
1940
1945
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
Nature 2001 Feb 15409(6822)860-921
Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHughW Funke R Gage D Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernanK Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovic N Subramanian A Wyman D Rogers J Sulston J AinscoughR Beck S Bentley D Burton J Clee C Carter N Coulson A Deadman R Deloukas P Dunham ADunhamI Durbin R French L Grafham D Gregory S Hubbard T Humphray S Hunt A Jones M Lloyd C McMurrayA Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R SimsS Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER Fulton LA ChinwallaAT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenningS Slezak T Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA MuznyDM Scherer SE Bouck JB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML NaylorSL Kucherlapati RS Nelson DL Weinstock GM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A ItohT Kawagoe C Watanabe H Totoki YTaylor T Weissenbach J Heilig R Saurin W Artiguenave F BrottierP Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-Stamm L Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H Yu J Wang J HuangG Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K Minoshima S Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J LehrachH Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G AgarwalaR Aravind LBailey JA Bateman A Batzoglou S Birney E Bork P Brown DG Burge CB Cerutti L ChenHC Church D Clamp M Copley RR Doerks T Eddy SR Eichler EE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA KasifS Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF StupkaESzustakowski J Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ Osoegawa K Shizuya H Choi S Chen YJ International Human GenomeSequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones
452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)
bull European Molecular Biology Laboratory (EMBL) de datos de Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)
bull DNA Data Bank de Japoacuten (DDBJ)
bull Reciben las secuencias producidas en laboratorios de todo el mundo de maacutes de 100000 organismos distintos
bull Crece a un ritmo exponencial duplicando cada 10 meses Suelte 134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
0
100000
200000
300000
400000
500000
600000
700000
800000
1865
1870
1875
1880
1885
1890
1895
1900
1905
1910
1915
1920
1925
1930
1935
1940
1945
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
Nature 2001 Feb 15409(6822)860-921
Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHughW Funke R Gage D Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernanK Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovic N Subramanian A Wyman D Rogers J Sulston J AinscoughR Beck S Bentley D Burton J Clee C Carter N Coulson A Deadman R Deloukas P Dunham ADunhamI Durbin R French L Grafham D Gregory S Hubbard T Humphray S Hunt A Jones M Lloyd C McMurrayA Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R SimsS Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER Fulton LA ChinwallaAT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenningS Slezak T Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA MuznyDM Scherer SE Bouck JB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML NaylorSL Kucherlapati RS Nelson DL Weinstock GM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A ItohT Kawagoe C Watanabe H Totoki YTaylor T Weissenbach J Heilig R Saurin W Artiguenave F BrottierP Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-Stamm L Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H Yu J Wang J HuangG Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K Minoshima S Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J LehrachH Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G AgarwalaR Aravind LBailey JA Bateman A Batzoglou S Birney E Bork P Brown DG Burge CB Cerutti L ChenHC Church D Clamp M Copley RR Doerks T Eddy SR Eichler EE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA KasifS Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF StupkaESzustakowski J Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ Osoegawa K Shizuya H Choi S Chen YJ International Human GenomeSequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
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bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
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DGAPA UNAM
Proyecto PAPIME PE 201509
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Commons
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Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)
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httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
Nature 2001 Feb 15409(6822)860-921
Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHughW Funke R Gage D Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernanK Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovic N Subramanian A Wyman D Rogers J Sulston J AinscoughR Beck S Bentley D Burton J Clee C Carter N Coulson A Deadman R Deloukas P Dunham ADunhamI Durbin R French L Grafham D Gregory S Hubbard T Humphray S Hunt A Jones M Lloyd C McMurrayA Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R SimsS Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER Fulton LA ChinwallaAT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenningS Slezak T Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA MuznyDM Scherer SE Bouck JB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML NaylorSL Kucherlapati RS Nelson DL Weinstock GM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A ItohT Kawagoe C Watanabe H Totoki YTaylor T Weissenbach J Heilig R Saurin W Artiguenave F BrottierP Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-Stamm L Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H Yu J Wang J HuangG Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K Minoshima S Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J LehrachH Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G AgarwalaR Aravind LBailey JA Bateman A Batzoglou S Birney E Bork P Brown DG Burge CB Cerutti L ChenHC Church D Clamp M Copley RR Doerks T Eddy SR Eichler EE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA KasifS Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF StupkaESzustakowski J Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ Osoegawa K Shizuya H Choi S Chen YJ International Human GenomeSequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
Nature 2001 Feb 15409(6822)860-921
Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHughW Funke R Gage D Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernanK Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovic N Subramanian A Wyman D Rogers J Sulston J AinscoughR Beck S Bentley D Burton J Clee C Carter N Coulson A Deadman R Deloukas P Dunham ADunhamI Durbin R French L Grafham D Gregory S Hubbard T Humphray S Hunt A Jones M Lloyd C McMurrayA Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R SimsS Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER Fulton LA ChinwallaAT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenningS Slezak T Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA MuznyDM Scherer SE Bouck JB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML NaylorSL Kucherlapati RS Nelson DL Weinstock GM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A ItohT Kawagoe C Watanabe H Totoki YTaylor T Weissenbach J Heilig R Saurin W Artiguenave F BrottierP Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-Stamm L Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H Yu J Wang J HuangG Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K Minoshima S Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J LehrachH Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G AgarwalaR Aravind LBailey JA Bateman A Batzoglou S Birney E Bork P Brown DG Burge CB Cerutti L ChenHC Church D Clamp M Copley RR Doerks T Eddy SR Eichler EE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA KasifS Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF StupkaESzustakowski J Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ Osoegawa K Shizuya H Choi S Chen YJ International Human GenomeSequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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1965
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1980
1985
1990
1995
2000
2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
Nature 2001 Feb 15409(6822)860-921
Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHughW Funke R Gage D Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernanK Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovic N Subramanian A Wyman D Rogers J Sulston J AinscoughR Beck S Bentley D Burton J Clee C Carter N Coulson A Deadman R Deloukas P Dunham ADunhamI Durbin R French L Grafham D Gregory S Hubbard T Humphray S Hunt A Jones M Lloyd C McMurrayA Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R SimsS Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER Fulton LA ChinwallaAT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenningS Slezak T Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA MuznyDM Scherer SE Bouck JB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML NaylorSL Kucherlapati RS Nelson DL Weinstock GM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A ItohT Kawagoe C Watanabe H Totoki YTaylor T Weissenbach J Heilig R Saurin W Artiguenave F BrottierP Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-Stamm L Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H Yu J Wang J HuangG Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K Minoshima S Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J LehrachH Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G AgarwalaR Aravind LBailey JA Bateman A Batzoglou S Birney E Bork P Brown DG Burge CB Cerutti L ChenHC Church D Clamp M Copley RR Doerks T Eddy SR Eichler EE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA KasifS Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF StupkaESzustakowski J Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ Osoegawa K Shizuya H Choi S Chen YJ International Human GenomeSequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
0
100000
200000
300000
400000
500000
600000
700000
800000
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1910
1915
1920
1925
1930
1935
1940
1945
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
Nature 2001 Feb 15409(6822)860-921
Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHughW Funke R Gage D Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernanK Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovic N Subramanian A Wyman D Rogers J Sulston J AinscoughR Beck S Bentley D Burton J Clee C Carter N Coulson A Deadman R Deloukas P Dunham ADunhamI Durbin R French L Grafham D Gregory S Hubbard T Humphray S Hunt A Jones M Lloyd C McMurrayA Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R SimsS Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER Fulton LA ChinwallaAT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenningS Slezak T Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA MuznyDM Scherer SE Bouck JB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML NaylorSL Kucherlapati RS Nelson DL Weinstock GM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A ItohT Kawagoe C Watanabe H Totoki YTaylor T Weissenbach J Heilig R Saurin W Artiguenave F BrottierP Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-Stamm L Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H Yu J Wang J HuangG Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K Minoshima S Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J LehrachH Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G AgarwalaR Aravind LBailey JA Bateman A Batzoglou S Birney E Bork P Brown DG Burge CB Cerutti L ChenHC Church D Clamp M Copley RR Doerks T Eddy SR Eichler EE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA KasifS Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF StupkaESzustakowski J Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ Osoegawa K Shizuya H Choi S Chen YJ International Human GenomeSequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
Nature 2001 Feb 15409(6822)860-921
Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHughW Funke R Gage D Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernanK Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovic N Subramanian A Wyman D Rogers J Sulston J AinscoughR Beck S Bentley D Burton J Clee C Carter N Coulson A Deadman R Deloukas P Dunham ADunhamI Durbin R French L Grafham D Gregory S Hubbard T Humphray S Hunt A Jones M Lloyd C McMurrayA Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R SimsS Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER Fulton LA ChinwallaAT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenningS Slezak T Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA MuznyDM Scherer SE Bouck JB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML NaylorSL Kucherlapati RS Nelson DL Weinstock GM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A ItohT Kawagoe C Watanabe H Totoki YTaylor T Weissenbach J Heilig R Saurin W Artiguenave F BrottierP Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-Stamm L Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H Yu J Wang J HuangG Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K Minoshima S Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J LehrachH Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G AgarwalaR Aravind LBailey JA Bateman A Batzoglou S Birney E Bork P Brown DG Burge CB Cerutti L ChenHC Church D Clamp M Copley RR Doerks T Eddy SR Eichler EE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA KasifS Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF StupkaESzustakowski J Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ Osoegawa K Shizuya H Choi S Chen YJ International Human GenomeSequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
Definiciones
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientific data information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
Cyberinfrastructure
bull Describes the new research environments that support advanceddata acquisition data storage data management data integration data mining data visualization and other computing and informationprocessing services over the Internet (NSF 2003)
bull The comprehensive infrastructure needed to capitalize on dramatic advances in information Technology Integrates hardware for computing data and networks digitally-enabled sensors observatories and experimental facilities and an interoperable suite of software and middle-ware services and tools Investments in interdiscip-linary teams and cyberinfrastructure professionals with expertise in algorithm development system operations and applications development are also essential to exploit the full power of cyberinfrastructure to create disseminate and preserve scientificdata information and knowledge (NSF 2007)
bull Technological solution to the problem of efficiently connecting data computers and people with the goal of enabling derivation of novel scientific theories and knowledge (Wikipedia 2009)
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
Ciberinfraestructura
bull Infraestructura electroacutenicandash Sistemas computacionales
ndash Sensores digitales instrumentos
ndash Redes
bull Softwarendash Aplicaciones
ndash Utilidades
ndash Herramientas
ndash Servicios
bull Colecciones de datos y datos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndashall three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de
las TIC y abarca nuevas metodologiacuteas de investigacioacuten que salen de un mayor
acceso a
ndash Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y
las instalaciones redes de sensores y repositorios de datos
ndash Software y servicios de infraestructura que permitan garantizar la conectividad e
interoperabilidad
ndash Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y
herramientas de interaccioacuten
ndash Avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de
investigacioacuten
bull Permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes
creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la
investigacioacuten con un mayor efecto
bull Colaboracioacuten
bull Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea
de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de
intercambio de recursos
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
e-investigacioacuten
bull e-journal electronic
bull e-social sciences de enabling (permitir)
(National Centre for e-Social Science
2008)
bull e- research alta velocidad red digital
disponible a cualquir hora en cualquier
lugar (Anderson y Kanuka 2002)
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
ndash Computer
ndash Internet
ndash Databases
ndash Collaboratories
ndash Reservories
ndash Grid
bull Resources
bull Tools
bull Services
e-researche-science amp Cyberinfrastructure
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
e-research
bull resources
bull tools
bull services
bull retrival
bull managment
bull analysis
bull customize
bull control
bull automatic
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
bull Colaboratorio fusioacuten de colaboracioacuten y
laboratorio ha sido acuntildeada para definir
la combinacioacuten
bull Repositorio coleccioacuten de e-prints
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
Proyectos
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
E-investigacioacuten bibliograacutefica
bull Investigacioacuten bibliograacutefica basada en el
uso de la Web y la ciberinfraestructura
ndash Recursos de la Web 20 en evolucioacuten a la 30
ndash Aplicaciones herramientas servicios
ndash Colecciones de datos digitales (repositorios
bases de datos)
bull Anaacutelisis sisteacutemico de la literatura
bull Meta-anaacutelisis
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
Tareas
bull Buscar tres ejemplos de e-ciencia
(ciberinfraestructura) de su aacuterea de
intereacutes
bull Marcarlo en Diigo y compartirlo al grupo
bull Describir uno de ellos en una cuartilla
bull Enviarlo al grupo en documento google
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
bull Este proyecto se lleva a cabo gracias al
financiamiento de
DGAPA UNAM
Proyecto PAPIME PE 201509
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
Licencia Creative
Commons
httpcreativecommonsorglicensesby30deedes_GT
Michaacuten L 2011 Presentacioacuten
Forma de citar este trabajo
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