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A bicluster is a subset of genes that show similar behavior within a subset of conditions. Biclustering algorithm is a useful tool to uncover groups of genes involved in the same cellular process and groups of conditions which take place in this process. We are proposing a polynomial time algorithm to identify functionally highly correlated biclusters. Our algorithm identifies (1) the gene set that follows additive, multiplicative, and combined patterns simultaneously that allow high level of noise, (2) the multiple, possibly overlapped, and diverse gene sets, (3) biclusters with negatively correlated as well as positively correlated gene set simultaneously, and (4) gene sets whose functional association is strongly high. We validated the level of functional association of our method, and compared with current methods using GO.
Date of Conference: June 29 2008-July 5 2008