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Nat Genet. 2003 Jun;34(2):166-76.

Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data.

Author information

1
Computer Science Department, Stanford University, Stanford, California, 94305, USA. eran@cs.stanford.edu

Abstract

Much of a cell's activity is organized as a network of interacting modules: sets of genes coregulated to respond to different conditions. We present a probabilistic method for identifying regulatory modules from gene expression data. Our procedure identifies modules of coregulated genes, their regulators and the conditions under which regulation occurs, generating testable hypotheses in the form 'regulator X regulates module Y under conditions W'. We applied the method to a Saccharomyces cerevisiae expression data set, showing its ability to identify functionally coherent modules and their correct regulators. We present microarray experiments supporting three novel predictions, suggesting regulatory roles for previously uncharacterized proteins.

PMID:
12740579
DOI:
10.1038/ng1165
[Indexed for MEDLINE]

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