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International Journal Of Bilogical Sciences

.: Home > International Journal Of Bilogical Sciences > 2014 > Volume 10 Number 7 > Lei Yang1,2, Xudong Zhao1, Xianglong Tang1

Predicting Disease-Related Proteins Based on Clique Backbone in Protein-Protein Interaction Network

Lei Yang1,2, Xudong Zhao1, Xianglong Tang1
1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China; 2. Information and Network Management Centre, Heilongjiang University, Harbin, China.  Corresponding author:
Abstract :

Network biology integrates different kinds of data, including physical or functional networks and disease gene sets, to interpret human disease. A clique (maximal complete subgraph) in a protein-protein interaction network is a topological module and possesses inherently biological significance. A disease-related clique possibly associates with complex diseases. Fully identifying disease components in a clique is conductive to uncovering disease mechanisms. This paper proposes an approach of predicting disease proteins based on cliques in a protein-protein interaction network. To tolerate false positive and negative interactions in protein networks, extending cliques and scoring predicted disease proteins with gene ontology terms are introduced to the clique-based method. Precisions of predicted disease proteins are verified by disease phenotypes and steadily keep to more than 95%. The predicted disease proteins associated with cliques can partly complement mapping between genotype and phenotype, and provide clues for understanding the pathogenesis of serious diseases.

Keywords :
predicting disease proteins, clique centrality analysis, association with complex diseases, data integration, protein-protein interaction networks.

Date Deposited : 12 Feb 2016 10:01

Last Modified : 12 Feb 2016 10:01

Official URL:

Volume 10, Number 7, - 2014 , ISSN 1449-2288

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