NCBI GEO: archive for high-throughput functional genomic data.

NCBI GEO: archive for high-throughput functional genomic data.
复制标题

DOI:
10.1093/nar/gkn764
复制
发表时间:
2009-01
影响因子:
14.9
通讯作者:
Edgar R
Edgar R
中科院分区:
生物学2区
文献类型:
--
作者:
Barrett T;Troup DB;Wilhite SE;Ledoux P;Rudnev D;Evangelista C;Kim IF;Soboleva A;Tomashevsky M;Marshall KA;Phillippy KH;Sherman PM;Muertter RN;Edgar R

文献摘要

参考文献

被引文献

相似文献

国家生物技术信息中心(NCBI)的基因表达综合(GEO)是高通量基因表达数据的最大公共存储库。数量变化,染色质结构,甲基化状态和转录因子结合。诸如微阵列之类的技术以及最近的下一代测序。迈阿密)。从基因中心和以实验为中心的角度分析和下载表达数据。 .nlm.nih.gov/geo/。
The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest public repository for high-throughput gene expression data. Additionally, GEO hosts other categories of high-throughput functional genomic data, including those that examine genome copy number variations, chromatin structure, methylation status and transcription factor binding. These data are generated by the research community using high-throughput technologies like microarrays and, more recently, next-generation sequencing. The database has a flexible infrastructure that can capture fully annotated raw and processed data, enabling compliance with major community-derived scientific reporting standards such as ‘Minimum Information About a Microarray Experiment’ (MIAME). In addition to serving as a centralized data storage hub, GEO offers many tools and features that allow users to effectively explore, analyze and download expression data from both gene-centric and experiment-centric perspectives. This article summarizes the GEO repository structure, content and operating procedures, as well as recently introduced data mining features. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.
NCBI GEO:开采数以百万计的表达概况 - 数据库和工具更新。
DOI: 10.1093/nar/gkl887
发表时间: 2007-01
影响因子: 14.9
作者:
Barrett, Tanya;Troup, Dennis B.;Wilhite, Stephen E.;Ledoux, Pierre;Rudnev, Dmitry;Evangelista, Carlos;Kim, Irene F.;Soboleva, Alexandra;Tomashevsky, Maxim;Edgar, Ron
通讯作者: Edgar, Ron
DOI: 10.1093/nar/gkm1000
发表时间: 2008-01
影响因子: 14.9
作者:
Wheeler, David L.;Barrett, Tanya;Benson, Dennis A.;Bryant, Stephen H.;Canese, Kathi;Chetvernin, Vyacheslav;Church, Deanna M.;DiCuccio, Michael;Edgar, Ron;Federhen, Scott;Feolo, Michael;Geer, Lewis Y.;Helmberg, Wolfgang;Kapustin, Yuri;Khovayko, Oleg;Landsman, David;Lipman, David J.;Madden, Thomas L.;Maglott, Donna R.;Miller, Vadim;Ostell, James;Pruitt, Kim D.;Schuler, Gregory D.;Shumway, Martin;Sequeira, Edwin;Sherry, Steven T.;Sirotkin, Karl;Souvorov, Alexandre;Starchenko, Grigory;Tatusov, Roman L.;Tatusova, Tatiana A.;Wagner, Lukas;Yaschenko, Eugene
通讯作者: Yaschenko, Eugene
DOI: 10.1093/nar/30.1.207
发表时间: 2002-01-01
影响因子: 14.9
作者:
Edgar, R;Domrachev, M;Lash, AE
通讯作者: Lash, AE
DOI: 10.1038/nature07107
发表时间: 2008-08-07
期刊: NATURE
影响因子: 64.8
作者:
Meissner, Alexander;Mikkelsen, Tarjei S.;Gu, Hongcang;Wernig, Marius;Hanna, Jacob;Sivachenko, Andrey;Zhang, Xiaolan;Bernstein, Bradley E.;Nusbaum, Chad;Jaffe, David B.;Gnirke, Andreas;Jaenisch, Rudolf;Lander, Eric S.
通讯作者: Lander, Eric S.
DOI: 10.1093/bioinformatics/btm254
发表时间: 2007-07-15
期刊: BIOINFORMATICS
影响因子: 5.8
作者:
Sean, Davis;Meltzer, Paul S.
通讯作者: Meltzer, Paul S.