A New Method for Recognizing Protein Complexes Based on Protein Interaction Networks and GO Terms

Motivation: A protein complex is the combination of proteins which interact with each other. Protein protein interaction (PPI) networks are composed of multiple protein complexes. It is very difficult to recognize protein complexes from PPI data due to the noise of PPI. Results: We proposed a new method, called Topology and Semantic Similarity Network (TSSN), based on topological structure characteristics and biological characteristics to construct the PPI. Experiments show that the TSSN can filter the noise of PPI data. We proposed a new algorithm, called Neighbor Nodes of Proteins (NNP), for recognizing protein complexes by considering their topology information. Experiments show that the algorithm can identify more protein complexes and more accurately. The recognition of protein complexes is vital in research on evolution analysis. Availability and implementation: https://github.com/bioinformatical-code/NNP.

Automated summary

The study introduced the TSSN method for constructing PPI networks and proposed the NNP algorithm for identifying protein complexes, which can accurately filter PPI data noise and identify more protein complexes.