title: Detecting protein complexes based on relevancy from protein interaction networks.
abstract: In protein-protein interaction networks, proteins combine into macromolecular complexes to execute essential functions in the cells, such as replication, transcription, protein transport. To solve the problem of detecting protein complexes from protein interaction networks, we used relevant graph and irrelevant graph to represent the relation of connection between a node and a core graph. We defined a variable Relevancy to represent whether a node had a dense or loose connection to a core graph. Then we proposed the Relevancy Judgment algorithm to detecting protein complexes from protein interaction networks. Our algorithm decided whether a node belonged to a protein complex through judging the relevancy between core graph and nodes out of core graph. Experiment results show that our algorithm has an excellent performance in both accuracy and hit rate.
authors.affiliation: Department of Computer Science, Central China Normal University, Wuhan, 430079, China, redcaryao@263.net.
authors.forename: Hua-Xiong
authors.initials: HX
authors.lastname: Yao
authors.forename: Yan
authors.initials: Y
authors.lastname: Yang
authors.forename: Xiao-Long
authors.initials: XL
authors.lastname: Li
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D025941:Protein Interaction Mapping; D060066:Protein Interaction Maps