title: Identification of protein complexes from multi-relationship protein interaction networks.
abstract: Protein complexes play an important role in biological processes. Recent developments in experiments have resulted in the publication of many high-quality, large-scale protein-protein interaction (PPI) datasets, which provide abundant data for computational approaches to the prediction of protein complexes. However, the precision of protein complex prediction still needs to be improved due to the incompletion and noise in PPI networks.
  
  
  
  There exist complex and diverse relationships among proteins after integrating multiple sources of biological information. Considering that the influences of different types of interactions are not the same weight for protein complex prediction, we construct a multi-relationship protein interaction network (MPIN) by integrating PPI network topology with gene ontology annotation information. Then, we design a novel algorithm named MINE (identifying protein complexes based on Multi-relationship protein Interaction NEtwork) to predict protein complexes with high cohesion and low coupling from MPIN.
  
  
  
  The experiments on yeast data show that MINE outperforms the current methods in terms of both accuracy and statistical significance.
authors.affiliation: School of Information Science and Engineering, Central South University, Changsha, 410083, China.|Department of Information and Computing Science, Changsha University, Changsha, 410003, China.
authors.forename: Xueyong
authors.initials: X
authors.lastname: Li
authors.affiliation: School of Information Science and Engineering, Central South University, Changsha, 410083, China. jxwang@mail.csu.edu.cn.
authors.forename: Jianxin
authors.initials: J
authors.lastname: Wang
authors.affiliation: Department of Information and Computing Science, Changsha University, Changsha, 410003, China. bihaizhao@163.com.
authors.forename: Bihai
authors.initials: B
authors.lastname: Zhao
authors.affiliation: Department of Mechanical Engineering and Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, SK, S7N 5A9, Canada.
authors.forename: Fang-Xiang
authors.initials: FX
authors.lastname: Wu
authors.affiliation: Department of Computer Science, Georgia State University, Atlanta, GA, 30302-4110, USA.
authors.forename: Yi
authors.initials: Y
authors.lastname: Pan
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D063990:Gene Ontology; D025941:Protein Interaction Mapping / Q000379:methods*; D060066:Protein Interaction Maps; D011506:Proteins / Q000235:genetics / Q000378:metabolism; D015203:Reproducibility of Results
chemical_list: D011506:Proteins