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BMCBI
2010

Inference of sparse combinatorial-control networks from gene-expression data: a message passing approach

8 years 7 months ago
Inference of sparse combinatorial-control networks from gene-expression data: a message passing approach
Background: Transcriptional gene regulation is one of the most important mechanisms in controlling many essential cellular processes, including cell development, cell-cycle control, and the cellular response to variations in environmental conditions. Genes are regulated by transcription factors and other genes/proteins via a complex interconnection network. Such regulatory links may be predicted using microarray expression data, but most regulation models suppose transcription factor independence, which leads to spurious links when many genes have highly correlated expression levels. Results: We propose a new algorithm to infer combinatorial control networks from gene-expression data. Based on a simple model of combinatorial gene regulation, it includes a message-passing approach which avoids explicit sampling over putative gene-regulatory networks. This algorithm is shown to recover the structure of a simple artificial cell-cycle network model for baker's yeast. It is then appli...
Marc Bailly-Bechet, Alfredo Braunstein, Andrea Pag
Added 08 Dec 2010
Updated 08 Dec 2010
Type Journal
Year 2010
Where BMCBI
Authors Marc Bailly-Bechet, Alfredo Braunstein, Andrea Pagnani, Martin Weigt, Riccardo Zecchina
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