Variable neighborhood search for reverse engineering of gene regulatory networks

Display Omitted A search heuristic is proposed for reverse engineering of gene regulatory networks.The approach is based on the variable neighborhood search metaheuristic.Search neighborhood structures are defined based on permissible move types.Empirically it outperforms greedy techniques in both speed and solution quality. A new search heuristic, Divided Neighborhood Exploration Search, designed to be used with inference algorithms such as Bayesian networks to improve on the reverse engineering of gene regulatory networks is presented. The approach systematically moves through the search space to find topologies representative of gene regulatory networks that are more likely to explain microarray data. In empirical testing it is demonstrated that the novel method is superior to the widely employed greedy search techniques in both the quality of the inferred networks and computational time.