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BioMed Central, Genome Biology, 12(10), p. R139

DOI: 10.1186/gb-2009-10-12-r139

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

Journal article published in 2009 by Priit Adler, Raivo Kolde ORCID, Meelis Kull, Aleksandr Tkachenko, Hedi Peterson, Jüri Reimand, Jaak Vilo ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

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/ .