Zhang, X.Moret, B.M.E.2009-10-142009-10-142009-10-14200910.1007/978-3-642-04241-6_34https://infoscience.epfl.ch/handle/20.500.14299/43680WOS:000271458900034Computational inference of transcriptional regulatory networks remains a challenging problem, in part due to the lack of strong network models. In this paper we present evolutionary approaches to improve the inference of regulatory networks for a family of organisms by developing an evolutionary model for these networks and taking advantage of established phylogenetic relationships among these organisms. In previous work, we used a simple evolutionary model for regulatory networks and provided extensive simulation results showing that phylogenetic information, combined with such a model, could be used to gain significant improvements on the performance of current inference algorithms.GeneDuplicationReconstructionSequencesGrowthTreestext::conference output::conference proceedings::conference paper