关键词: 蛋白质相互作用网络, 模块度函数, 初始模块, 蛋白质复合物

Abstract: Aiming at the problem that the accuracy and recall of the protein complexes identification algorithm based on weighted modularity function clustering are not high and the running efficiency is low, a protein complex recognition algorithm named IWPC-MF（Algorithm for Identifying Weighted Protein Complexes based on Modularity Function） is proposed. Firstly, the edge clustering coefficient is improved by using the point clustering coefficient, and the weighted protein network is constructed by combining the Pearson correlation coefficient and the edge point clustering coefficient. Secondly, seed nodes are selected according to the weight of nodes, then the similarity measurement and the protein attachment degree between nodes are designed to obtain the initial clustering module by traversing neighbors of seeds. Finally, based on the tightness, the modularity function is designed to merge the initial module and finally complete the protein complex detection, which can overcome the defect that the traditional modularity function cannot identify the overlapped and small complex. IWPC-MF algorithm is used to identify protein complexes on DIP data. The experimental results show that IWPC-MF algorithm has better performance on accuracy and recall, which is more reasonable to identify protein complexes.

Key words: protein-protein interaction network, modularity function, initial module, protein complex