Revealing signaling pathway deregulation by using gene expression signatures and regulatory motif analysis.
Gene expression signatures consisting of tens to hundreds of genes have been found to be informative for different biological states. Recently, many computational methods have been proposed for biological interpretation of such signatures. However, there is a lack of methods for identifying cell signaling pathways whose deregulation results in an observed expression signature. We present a strategy for identifying such signaling pathways and evaluate the strategy using six human and mouse gene expression signatures.
Liu
Yingchun
Y
Computational Biology and Biological Physics, Department of Theoretical Physics, Lund University, SE-221 85, Sweden. spring@thep.lu.se
Ringnér
Markus
M
D000465:Algorithms; D000818:Animals; D001483:Base Sequence; D001665:Binding Sites / Q000235:genetics; D015415:Biomarkers; D030561:Databases, Nucleic Acid; D015870:Gene Expression; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D006801:Humans; D051379:Mice; D050436:Regulatory Elements, Transcriptional / Q000235:genetics*; D015398:Signal Transduction / Q000235:genetics*; D049490:Systems Biology
D015415:Biomarkers