Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods.
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/.
Adler
Priit
P
Institute of Molecular and Cell Biology, Riia 23, 51010 Tartu, Estonia. adler@ut.ee
Kolde
Raivo
R
Kull
Meelis
M
Tkachenko
Aleksandr
A
Peterson
Hedi
H
Reimand
Jüri
J
Vilo
Jaak
J
D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D020407:Internet; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data*; D012984:Software