Module Networks : Discovering Regulatory Modules and their Condition Specific Regulators from Gene Expression Data
Modules and their Condition Specific Regulators from Gene Expression Data Eran Segal , Michael Shapira, Aviv Regev, Dana Pe’er David Botstein, Daphne Koller , Nir Friedman Much of a cell's activity is organized as a network of interacting modules: sets of genes co-regulated to respond to different conditions. We present a probabilistic method for discovering regulatory modules from gene expression data. Our procedure identifies modules of co-regulated 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 dataset, demonstrating 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.