WCOACH: Protein complex prediction in weighted PPI networks

Abstract

Protein complexes are aggregates of protein molecules that play important roles in biological processes‎. ‎Detecting protein complexes from protein-protein interaction (PPI) networks is one of the most challenging problems in computational biology, and many computational methods have been developed to solve this problem‎. ‎Generally‎, ‎these methods yield high false positive rates‎.‎ In this article‎, a semantic similarity measure between proteins‎, ‎based on Gene Ontology (GO) structure‎, ‎is applied to weigh PPI networks. Consequently, one of the well-known methods, COACH, has been improved to be compatible with weighted PPI networks for protein complex detection. The new method, WCOACH, is compared to the COACH, ClusterOne, IPCA, CORE, OH-PIN, HC-PIN and MCODE methods on several PPI networks such as DIP, Krogan, Gavin 2002 and MIPS. ‎WCOACH can be applied as a fast and high-performance algorithm to predict protein complexes in weighted PPI networks‎. All data and programs are freely available at http://bioinformatics.aut.ac.ir/wcoach.