A Novel Protein Complex Identification Algorithm Based on the Integration of Local Network Topology and Gene Ontology

The identification of protein complexes is an essential step to understand the principles of cellular organization and biochemical phenomena. A large dataset of experimentally detected protein-protein interactions (PPI) has been determined using high-throughput experimental techniques. However, these datasets usually contain spurious interactions, which complicate the accurate identification of protein complexes by using computational methods. In this study, a novel method is developed to predict protein complexes based on PPI network topology and gene ontology. A protein functional similarity is performed to estimate the reliability of this interaction. A minimum cut-based method is used to detect protein complexes in the weight network. Experimental results show that our method performs better than several efficient, existing clustering algorithms.

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