NCBI GEO: archive for functional genomics data sets-update

被引:6871
|
作者
Barrett, Tanya [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 ]
Holko, Michelle [1 ]
Yefanov, Andrey [1 ]
Lee, Hyeseung [1 ]
Zhang, Naigong [1 ]
Robertson, Cynthia L. [1 ]
Serova, Nadezhda [1 ]
Davis, Sean [2 ]
Soboleva, Alexandra [1 ]
机构
[1] NCI, Natl Ctr Biotechnol Informat, Natl Lib Med, NIH, Bethesda, MD 20892 USA
[2] NCI, Mol Genet Sect, Genet Branch, NIH, Bethesda, MD 20892 USA
基金
美国国家卫生研究院;
关键词
GENE-EXPRESSION;
D O I
10.1093/nar/gks1193
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
The Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) is an international public repository for high-throughput microarray and next-generation sequence functional genomic data sets submitted by the research community. The resource supports archiving of raw data, processed data and metadata which are indexed, cross-linked and searchable. All data are freely available for download in a variety of formats. GEO also provides several web-based tools and strategies to assist users to query, analyse and visualize data. This article reports current status and recent database developments, including the release of GEO2R, an R-based web application that helps users analyse GEO data.
引用
收藏
页码:D991 / D995
页数:5
相关论文
共 18 条
  • [1] NCBI GEO: archive for functional genomics data sets-10 years on
    Barrett, Tanya
    Troup, Dennis B.
    Wilhite, Stephen E.
    Ledoux, Pierre
    Evangelista, Carlos
    Kim, Irene F.
    Tomashevsky, Maxim
    Marshall, Kimberly A.
    Phillippy, Katherine H.
    Sherman, Patti M.
    Muertter, Rolf N.
    Holko, Michelle
    Ayanbule, Oluwabukunmi
    Yefanov, Andrey
    Soboleva, Alexandra
    NUCLEIC ACIDS RESEARCH, 2011, 39 : D1005 - D1010
  • [2] Predicting Cancer Prognosis Using Functional Genomics Data Sets
    Das, Jishnu
    Gayvert, Kaitlyn
    Yu, Haiyuan
    CANCER INFORMATICS, 2014, 13 : 85 - 88
  • [3] From data to function: Functional modeling of poultry genomics data
    McCarthy, F. M.
    Lyons, E.
    POULTRY SCIENCE, 2013, 92 (09) : 2519 - 2529
  • [4] Muscle Gene Sets: a versatile methodological aid to functional genomics in the neuromuscular field
    Malatras, Apostolos
    Duguez, Stephanie
    Duddy, William
    SKELETAL MUSCLE, 2019, 9 (1)
  • [5] Muscle Gene Sets: a versatile methodological aid to functional genomics in the neuromuscular field
    Apostolos Malatras
    Stephanie Duguez
    William Duddy
    Skeletal Muscle, 9
  • [6] MasterPATH: network analysis of functional genomics screening data
    Rubanova, Natalia
    Pinna, Guillaume
    Kropp, Jeremie
    Campalans, Anna
    Radicella, Juan Pablo
    Polesskaya, Anna
    Harel-Bellan, Annick
    Morozova, Nadya
    BMC GENOMICS, 2020, 21 (01)
  • [7] Integrating ChIP-seq with other functional genomics data
    Jiang, Shan
    Mortazavi, Ali
    BRIEFINGS IN FUNCTIONAL GENOMICS, 2018, 17 (02) : 104 - 115
  • [8] Functional genomics data: privacy risk assessment and technological mitigation
    Gursoy, Gamze
    Li, Tianxiao
    Liu, Susanna
    Ni, Eric
    Brannon, Charlotte M.
    Gerstein, Mark B.
    NATURE REVIEWS GENETICS, 2022, 23 (04) : 245 - 258
  • [9] Plant functional genomics: opportunities in microarray databases and data mining
    Kennedy, GC
    Wilson, IW
    FUNCTIONAL PLANT BIOLOGY, 2004, 31 (04) : 295 - 314
  • [10] Integrative Data Mining in Functional Genomics of Brassica napus and Arabidopsis thaliana
    Pan, Youlian
    Tchagangl, Alain
    Berube, Hugo
    Phan, Sieu
    Shearer, Heather
    Liu, Ziying
    Fobert, Pierre
    Famili, Faze
    TRENDS IN APPLIED INTELLIGENT SYSTEMS, PT III, PROCEEDINGS, 2010, 6098 : 92 - +