Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset
Abstract Background Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction.When only Trigger Module static data are available, gene interactions may be modelled by a Bayesian Network (BN) that represents the presence of direct interactions from regulators to regulees by conditional probab