Predicting disease-related proteins based on clique backbone in protein-protein interaction network.

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 pre

SUBMITTER: Yang L 

PROVIDER: S-EPMC4081603 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature