Bayesian Decomposition

Gene chips and gene expression microarrays offer the opportunity to study biological systems on a genome-wide basis, exploring the full transcriptional response in an experiment or therapy. Because of the complexity of living organisms, these transcriptional responses are complex, with multiple, overlapping groups of genes being expressed in response to continuing internal and external stimuli. In order to use expression measurements to identify upstream modifications in signaling pathways, it is necessary to disentangle these overlapping responses. Bayesian Decomposition provides a method of identifying such overlap and correctly assigning genes to multiple groups, allowing easier identification of pathway modifications. Here the results of the application of Bayesian Decomposition to cell cycle data are shown.