RECONSTRUCTION OF GENE NETWORKS USING PHENOMIC ALGORITHMS

The reconstruction of gene networks has become an important activity in Systems Biology. The potentialfor better methods of drug discovery and disease diagnosis hinges upon our understanding of theinteraction networks between the genes. Evolutionary methods are proving to be successful in suchproblems and a number of such methods have been proposed. However, all these methods are based onprocessing of genotypic information. We present evolutionary algorithms for reconstructing genenetworks from expression data using phenotypic interactions, thereby avoiding the need for an explicitobjective function. Specifically, we implement the Phenomic algorithm and validate it for thereconstruction of gene networks. We also extend the basic phenomic algorithm to perform multiobjectiveoptimization for gene network reconstruction. We apply both these algorithms to the yeast sporulationdataset and show that the algorithms can effectively identify gene networks. Both the algorithms arevalidated for stability and accuracy in the reconstruction of gene networks