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

Genome Biol. 2009;10(12):R139. doi: 10.1186/gb-2009-10-12-r139. Epub 2009 Dec 4.


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

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods*
  • Databases, Genetic*
  • Internet*
  • Oligonucleotide Array Sequence Analysis / statistics & numerical data*
  • Software*