Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods

被引：129

作者：

Adler, Priit ^{[1
]}

Kolde, Raivo ^{[2
,3
]}

Kull, Meelis ^{[2
,3
]}

Tkachenko, Aleksandr ^{[2
,3
]}

Peterson, Hedi ^{[1
,3
]}

Reimand, Jueri ^{[2
]}

Vilo, Jaak ^{[2
,3
]}

机构：

[1] Inst Mol & Cell Biol, EE-51010 Tartu, Estonia

[2] Univ Tartu, Inst Comp Sci, EE-50409 Tartu, Estonia

[3] Quretec, EE-51003 Tartu, Estonia

来源：

GENOME BIOLOGY | 2009年 / 10卷 / 12期

关键词：

EMBRYONIC STEM-CELLS; GENE-EXPRESSION PROFILES; MICROARRAY DATA; NETWORK RECONSTRUCTION; FUNCTIONAL ANNOTATION; DNA-REPLICATION; CANCER-CELLS; PROBE LEVEL; IDENTIFICATION; MAINTENANCE;

D O I：

10.1186/gb-2009-10-12-r139

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

We present a web resource MEM (Multi-Experiment Matrix) for gene expression similarity searches across many datasets. MEM features large collections of microarray datasets and utilizes rank aggregation to merge information from different datasets into a single global ordering with simultaneous statistical significance estimation. Unique features of MEM include automatic detection, characterization and visualization of datasets that includes the strongest coexpression patterns. MEM is freely available at http://biit.cs.ut.ee/mem/.

引用

页数：11

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