WCOACH: Protein complex prediction in weighted PPI networks

Genes & Genetic Systems
Morteza KouhsarYousef Jamali

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.

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Citations

Sep 8, 2016·Expert Review of Proteomics·Elena L RudashevskayaStavroula Markoutsa
Jan 3, 2018·Molecules : a Journal of Synthetic Chemistry and Natural Product Chemistry·Jie WangJiye Liang
Jan 7, 2020·Molecular Biology and Evolution·Andrew Ying-Fei Chang, Ben-Yang Liao
May 10, 2017·EURASIP Journal on Bioinformatics & Systems Biology·Danila VellaDario Di Silvestre
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Apr 5, 2018·Scientific Reports·Danila VellaRiccardo Bellazzi
Feb 26, 2019·Journal of Bioinformatics and Computational Biology·Wei ZhangXiufen Zou
Jun 20, 2018·Molecules : a Journal of Synthetic Chemistry and Natural Product Chemistry·Buwen CaoGuanghui Li

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