NCBI GEO: archive for functional genomics data sets-10 years on

被引:723
作者
Barrett, Tanya [1 ]
Troup, Dennis B. [1 ]
Wilhite, Stephen E. [1 ]
Ledoux, Pierre [1 ]
Evangelista, Carlos [1 ]
Kim, Irene F. [1 ]
Tomashevsky, Maxim [1 ]
Marshall, Kimberly A. [1 ]
Phillippy, Katherine H. [1 ]
Sherman, Patti M. [1 ]
Muertter, Rolf N. [1 ]
Holko, Michelle [1 ]
Ayanbule, Oluwabukunmi [1 ]
Yefanov, Andrey [1 ]
Soboleva, Alexandra [1 ]
机构
[1] NIH, Natl Ctr Biotechnol Informat, Natl Lib Med, Bethesda, MD 20892 USA
基金
美国国家卫生研究院;
关键词
GENE-EXPRESSION; INFORMATION;
D O I
10.1093/nar/gkq1184
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
A decade ago, the Gene Expression Omnibus (GEO) database was established at the National Center for Biotechnology Information (NCBI). The original objective of GEO was to serve as a public repository for high-throughput gene expression data generated mostly by microarray technology. However, the research community quickly applied microarrays to non-gene-expression studies, including examination of genome copy number variation and genome-wide profiling of DNA-binding proteins. Because the GEO database was designed with a flexible structure, it was possible to quickly adapt the repository to store these data types. More recently, as the microarray community switches to next-generation sequencing technologies, GEO has again adapted to host these data sets. Today, GEO stores over 20 000 microarray- and sequence-based functional genomics studies, and continues to handle the majority of direct high-throughput data submissions from the research community. Multiple mechanisms are provided to help users effectively search, browse, download and visualize the data at the level of individual genes or entire studies. This paper describes recent database enhancements, including new search and data representation tools, as well as a brief review of how the community uses GEO data. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.
引用
收藏
页码:D1005 / D1010
页数:6
相关论文
共 22 条
  • [1] [Anonymous], 2002, Nature, V419, P323
  • [2] NCBI GEO: archive for high-throughput functional genomic data
    Barrett, Tanya
    Troup, Dennis B.
    Wilhite, Stephen E.
    Ledoux, Pierre
    Rudnev, Dmitry
    Evangelista, Carlos
    Kim, Irene F.
    Soboleva, Alexandra
    Tomashevsky, Maxim
    Marshall, Kimberly A.
    Phillippy, Katherine H.
    Sherman, Patti M.
    Muertter, Rolf N.
    Edgar, Ron
    [J]. NUCLEIC ACIDS RESEARCH, 2009, 37 : D885 - D890
  • [3] Minimum information about a microarray experiment (MIAME) - toward standards for microarray data
    Brazma, A
    Hingamp, P
    Quackenbush, J
    Sherlock, G
    Spellman, P
    Stoeckert, C
    Aach, J
    Ansorge, W
    Ball, CA
    Causton, HC
    Gaasterland, T
    Glenisson, P
    Holstege, FCP
    Kim, IF
    Markowitz, V
    Matese, JC
    Parkinson, H
    Robinson, A
    Sarkans, U
    Schulze-Kremer, S
    Stewart, J
    Taylor, R
    Vilo, J
    Vingron, M
    [J]. NATURE GENETICS, 2001, 29 (04) : 365 - 371
  • [4] Simultaneous analysis of distinct Omics data sets with integration of biological knowledge: Multiple Factor Analysis approach
    de Tayrac, Marie
    Le, Sebastien
    Aubry, Marc
    Mosser, Jean
    Husson, Francois
    [J]. BMC GENOMICS, 2009, 10 : 32
  • [5] Global reconstruction of the human metabolic network based on genomic and bibliomic data
    Duarte, Natalie C.
    Becker, Scott A.
    Jamshidi, Neema
    Thiele, Ines
    Mo, Monica L.
    Vo, Thuy D.
    Srivas, Rohith
    Palsson, Bernhard O.
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2007, 104 (06) : 1777 - 1782
  • [6] Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
    Edgar, R
    Domrachev, M
    Lash, AE
    [J]. NUCLEIC ACIDS RESEARCH, 2002, 30 (01) : 207 - 210
  • [7] NCBI Epigenomics: a new public resource for exploring epigenomic data sets
    Fingerman, Ian M.
    McDaniel, Lee
    Zhang, Xuan
    Ratzat, Walter
    Hassan, Tarek
    Jiang, Zhifang
    Cohen, Robert F.
    Schuler, Gregory D.
    [J]. NUCLEIC ACIDS RESEARCH, 2011, 39 : D908 - D912
  • [8] Gene Expression Prediction by Soft Integration and the Elastic Net-Best Performance of the DREAM3 Gene Expression Challenge
    Gustafsson, Mika
    Hornquist, Michael
    [J]. PLOS ONE, 2010, 5 (02):
  • [9] Gene Expression-Based Classification of Non-Small Cell Lung Carcinomas and Survival Prediction
    Hou, Jun
    Aerts, Joachim
    den Hamer, Bianca
    van IJcken, Wilfred
    den Bakker, Michael
    Riegman, Peter
    van der Leest, Cor
    van der Spek, Peter
    Foekens, John A.
    Hoogsteden, Henk C.
    Grosveld, Frank
    Philipsen, Sjaak
    [J]. PLOS ONE, 2010, 5 (04):
  • [10] Bayesian approach to transforming public gene expression repositories into disease diagnosis databases
    Huang, Haiyan
    Liu, Chun-Chi
    Zhou, Xianghong Jasmine
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2010, 107 (15) : 6823 - 6828