Detection of Communities in the Yeast Protein-Protein Interaction Network Based on Graph Clustering

Abstract:

Interaction detection methods can led to the discovery of thousands of protein-protein interactions,and discerning relevance within large-scale data sets is important for bioinformation.As an important means for knowledge discovery,graph clustering attracts much attention in analysis of protein-protein interaction networks.Here,a modularity-based method was used to find communities of protein-protein interaction networks.Using this method,177 communities were detected from a network involving 11,855 interactions among 2617 proteins in yeast and annotated according to MIPS hierarchical functional categories.The results validated that these communities are indeed densely connected in sub-graphs.