title: CAMWI: Detecting protein complexes using weighted clustering coefficient and weighted density.
abstract: Detection of protein complexes is very important to understand the principles of cellular organization and function. Recently, large protein-protein interactions (PPIs) networks have become available using high-throughput experimental techniques. These networks make it possible to develop computational methods for protein complex detection. Most of the current methods rely on the assumption that protein complex as a module has dense structure. However complexes have core-attachment structure and proteins in a complex core share a high degree of functional similarity, so it expects that a core has high weighted density. In this paper we present a Core-Attachment based method for protein complex detection from Weighted PPI Interactions using clustering coefficient and weighted density. Experimental results show that the proposed method, CAMWI improves the accuracy of protein complex detection.
authors: Computer Engineering Department , Tarbiat Modares University, Tehran, Iran. Electronic address: amir.lakizadeh@modares.ac.ir.
authors: Amir
authors: A
authors: Lakizadeh
authors: Computer Engineering Department , Tarbiat Modares University, Tehran, Iran. Electronic address: sjalili@modares.ac.ir.
authors: Saeed
authors: S
authors: Jalili
authors: Department of Biotechnology, College of Science, University of Tehran, Tehran, Iran. Electronic address: marashi@ut.ac.ir.
authors: Sayed-Amir
authors: SA
authors: Marashi
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D005656:Fungal Proteins / Q000378:metabolism; D025941:Protein Interaction Mapping / Q000379:methods*; D060066:Protein Interaction Maps
chemical_list: D005656:Fungal Proteins
keywords: Clustering coefficient; Core-attachment structure; Graph weighted density; Protein complex