title: Identifying protein complexes based on the integration of PPI network and gene expression data.
abstract: Identification of protein complexes is crucial to understand principles of cellular organisation and predict protein functions. In this paper, a novel protein complex discovery algorithm IPCIPG is proposed based on the integration of Protein-Protein Interaction network (PPI network) and gene expression data. IPCIPG is a local search algorithm which has two versions: IPCIPG-n for identifying non-overlapping clusters and IPCIPG-o for detecting overlapping clusters. The experimental results on the yeast PPI network show that IPCIPG can identify protein complexes with specific biological meaning more effectively, precisely and comprehensively than six other algorithms: HUNTER, HC-PIN, CMC, SPICi, MOCDE and MCL.
authors: School of Information Science and Engineering, Central South University, Changsha 410083, China.
authors: Weijie
authors: W
authors: Chen
authors: School of Information Science and Engineering, Central South University, Changsha 410083, China.
authors: Min
authors: M
authors: Li
authors: School of Information Science and Engineering, Central South University, Changsha 410083, China.
authors: Xuehong
authors: X
authors: Wu
authors: School of Information Science and Engineering, Central South University, Changsha 410083, China.
authors: Jianxin
authors: J
authors: Wang
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods; D025941:Protein Interaction Mapping / Q000379:methods*; D012441:Saccharomyces cerevisiae / Q000378:metabolism*; D029701:Saccharomyces cerevisiae Proteins / Q000502:physiology*; D015398:Signal Transduction / Q000502:physiology*
chemical_list: D029701:Saccharomyces cerevisiae Proteins
keywords: PPI networks; bioinformatics; clusters; gene expression data; protein complexes; protein–protein interaction