Abstract: A bipartite graph-based cluster ensemble method that integrates gene ontology(GO) and gene expression data with protein-protein interaction(PPI) networks is proposed. In this method,all different views of biological information and three basic clustering methods are contributed to a bipartite graph that comprehensively represents the relationships between the objects in this problem,including the proteins and the meta-clusters from the basic cluster methods. Furthermore,consistent modules are extracted using a symmetric non-negative matrix factorization(NMF)-based graph partition method and overlapping results are achieved. Extensive experimental results show that this method is superior to the baseline methods; further analysis is addressed to discuss the benefits of integrating multiple biological information sources and diverse clustering methods.