Defining transcriptional networks through integrative modeling of mRNA expression and transcription factor binding data

Background: Functional genomics studies are yielding information about regulatory processes in the cell at an unprecedented scale. In the yeast S. cerevisiae, DNA microarrays have not only been used to measure the mRNA abundance for all genes under a variety of conditions but also to determine the occupancy of all promoter regions by a large number of transcription factors. The challenge is to extract useful information about the global regulatory network from these data. Results: We present MA-Networker, an algorithm that combines microarray data for mRNA expression and transcription factor occupancy to define the regulatory network of the cell. Multivariate regression analysis is used to infer the activity of each transcription factor, and the correlation across different conditions between this activity and the mRNA expression of a gene is interpreted as regulatory coupling strength. Applying our method to S. cerevisiae, we find that, on average, 58% of the genes whose promoter reg...

• Type: Journal
• Year: 2004
• Where: BMCBI
• Authors: Feng Gao, Barrett C. Foat, Harmen J. Bussemaker
• Keywords: BMCBI 2004, Promoter Region, Transcription Factor, Transcription Factor Deletion