Gene selection for microarray data classification via multi-objective graph theoretic-based method

Mehrdad Rostami, Saman Forouzandeh, Kamal Berahmand, Mina Soltani, Meisam Shahsavari, Mourad Oussalah

Abstract: Highlights•A novel gene selection method has been developed by integrating the concept of node centrality and community detection.•The main goal of this method is to select a subset of the genes with lowest similarity and highest dependency.•In this proposed method the optimal number of final gene set is determined automatically.•Experimental results showed that the proposed method has the best performance among different gene selection methods.•The results on five microarray datasets indicate that this method improves microarray data classification accuracy.