Protein complex identification based on weighted PPI network with multi-source information

Proteins form complexes to accomplish biological functions such as transcription of DNA, translation of mRNA and cell growth. Detection of protein complexes from protein-protein interaction (PPI) networks is the first step for the analysis of biological processes and pathways. Here, we propose a new framework by incorporating Gene Ontology (GO), amino acid background frequency (AABF) and data from von Mering (von Mering data) to identify protein complexes. Firstly, based on the semantic similarity of GO, we construct a weighted PPI network. Secondly, von Mering data is added to construct six types of weighted graphs. Lastly, by integrating density, diameter and cosine similarity, we define a new condition for clustering proteins in these weighted protein network by selecting specific node as key node. Comparison and analysis results indicate that our proposed method could achieve better performances than some classic existing approaches in regard to f-measure and precision. (C) 2019 Elsevier Ltd. All rights reserved.