A hybrid clustering algorithm for identifying modules in Protein-Protein Interaction networks.
Identifying modules in Protein-Protein Interaction (PPI) networks is important to understand the organisation of the cellular processes. In this paper, we present a novel algorithm combining Molecular Complex Detection (MCODE) with Girvan-Newman (GN) to identify modules in PPI networks. Our algorithm can accurately discover denser modules in large-scale protein interaction networks. We applied it to S. cerevisiae PPI networks and obtained high matching rate between the predicted modules and the known protein complexes in Munich Information Center for Protein Sequences (MIPS). The simulation results show that our algorithm provides an effective, reliable and scalable method of identifying modules in PPI networks.
School of Computer Science and Technology, Xidian University, Xi'an, 710071, China. yuliang@mti.xidian.edu.cn
Liang
L
Yu
Lin
L
Gao
Peng Gang
PG
Sun
D000465:Algorithms; D016000:Cluster Analysis; D025941:Protein Interaction Mapping / Q000379:methods*; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000378:metabolism*; D029701:Saccharomyces cerevisiae Proteins / Q000737:chemistry / Q000378:metabolism*
D029701:Saccharomyces cerevisiae Proteins