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PMID: 19961599 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't

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

Genome biology ·Vol. 10 ·No. 12 ·2009-00-00 ·Pages R139

Adler P, Kolde R, Kull M, Tkachenko A, Peterson H, Reimand J, Vilo J

Abstract

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/.

MeSH Terms
Computational Biology/methods Databases, Genetic Internet Oligonucleotide Array Sequence Analysis/statistics & numerical data Software
Authors & Affiliations
7 authors, click to expand affiliations / ORCID
Adler Priit
Institute of Molecular and Cell Biology, Riia 23, 51010 Tartu, Estonia. [email protected]
Kolde Raivo
Kull Meelis
Tkachenko Aleksandr
Peterson Hedi
Reimand Jüri
Vilo Jaak
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Article Info
Journal
Genome biology
Abbr.
Genome Biol
ISSN
1474-760X
DOI
10.1186/gb-2009-10-12-r139
Email
[email protected]
Published
2009-00-00
Epub
2009-00-04
Pages
R139
Language
English
Region
England
NLM ID
100960660
PMCID
PMC2812946
Subset
IM
External Links
PubMed source DOI: 10.1186/gb-2009-10-12-r139 PMC Full Text View journal details
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