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“School of Nano-Sciences”

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Paper   IPM / Nano-Sciences / 14464
School of Nano Science
  Title:   WCOACH: Protein complex prediction in weighted PPI networks
  Author(s): 
1.  Morteza Kouhsar
2.  Fatemeh Zare Mirakabad
3.  Yousef Jamali
  Status:   Published
  Journal: Genes & genetic systems
  No.:  5
  Vol.:  90
  Year:  2015
  Pages:   317-324
  Publisher(s):   PubMed
  Supported by:  IPM
  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.

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