Automated modelling of signal transduction networks

Background: Intracellular signal transduction is achieved by networks of proteins and small molecules that transmit information from the cell surface to the nucleus, where they ultimately effect transcriptional changes. Understanding the mechanisms cells use to accomplish this important process requires a detailed molecular description of the networks involved. Results: We have developed a computational approach for generating static models of signal transduction networks which utilizes protein-interaction maps generated from large-scale twohybrid screens and expression profiles from DNA microarrays. Networks are determined entirely by integrating protein-protein interaction data with microarray expression data, without prior knowledge of any pathway intermediates. In effect, this is equivalent to extracting subnetworks of the protein interaction dataset whose members have the most correlated expression profiles. Conclusion: We show that our technique accurately reconstructs MAP Kinas...

• Type: Journal
• Year: 2002
• Where: BMCBI
• Authors: Martin Steffen, Allegra Petti, John Aach, Patrik D'haeseleer, George M. Church
• Keywords: BMCBI 2002, Expression Profiles, Signal Transduction, Signal Transduction Networks