title: Mining Dense Overlapping Subgraphs in weighted protein-protein interaction networks.
abstract: Many methods have been proposed for mining protein complexes from a protein-protein interaction network; however, most of them focus on unweighted networks and cannot find overlapping protein complexes. Since one protein may serve different roles within different functional groups, mining overlapping protein complexes in a weighted protein-protein interaction network has attracted more and more attention recently. In this paper, we propose an effective method, called MDOS (Mining Dense Overlapping Subgraphs), for mining dense overlapping protein complexes (subgraphs) in a weighted protein-protein interaction network. The proposed method can integrate the information about known complexes into a weighted protein-protein interaction network to improve the mining results. The experiment results show that our method mines more known complexes and has higher sensitivity and accuracy than the CODENSE and MCL methods.
authors.affiliation: Department of Information Management, National Taiwan University, Taipei, Taiwan, ROC. jtlee@ntu.edu.tw
authors.forename: Anthony J T
authors.initials: AJ
authors.lastname: Lee
authors.forename: Ming-Chih
authors.initials: MC
authors.lastname: Lin
authors.forename: Chia-Ming
authors.initials: CM
authors.lastname: Hsu
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D005656:Fungal Proteins / Q000145:classification; D025941:Protein Interaction Mapping / Q000379:methods*; D040901:Proteomics / Q000379:methods*; D012441:Saccharomyces cerevisiae / Q000235:genetics
chemical_list: D005656:Fungal Proteins