idenPC-MIIP: identify protein complexes from weighted PPI networks using mutual important interacting partner relation

Protein complexes are key units for studying a cell system. During the past decades, the genome-scale protein-protein interaction (PPI) data have been determined by high-throughput approaches, which enables the identification of protein complexes from PPI networks. However, the high-throughput approaches often produce considerable fraction of false positive and negative samples. In this study, we propose the mutual important interacting partner relation to reflect the co-complex relationship of two proteins based on their interaction neighborhoods. In addition, a new algorithm called idenPC-MIIP is developed to identify protein complexes from weighted PPI networks. The experimental results on two widely used datasets show that idenPC-MIIP outperforms 17 state-of-the-art methods, especially for identification of small protein complexes with only two or three proteins.

Automated summary

Protein complexes are key units for studying a cell system, and high-throughput approaches have enabled the determination of PPI data. The proposed mutual important interacting partner relation and the new algorithm idenPC-MIIP show improved performance in identifying protein complexes compared to existing methods.