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Issue No.03 - May-June (2013 vol.10)
pp: 729-741
Yijia Zhang , Coll. of Comput. Sci. & Technol., Dalian Univ. of Technol., Dalian, China
Hongfei Lin , Coll. of Comput. Sci. & Technol., Dalian Univ. of Technol., Dalian, China
Zhihao Yang , Coll. of Comput. Sci. & Technol., Dalian Univ. of Technol., Dalian, China
Jian Wang , Coll. of Comput. Sci. & Technol., Dalian Univ. of Technol., Dalian, China
Yanpeng Li , Coll. of Comput. Sci. & Technol., Dalian Univ. of Technol., Dalian, China
Bo Xu , Coll. of Comput. Sci. & Technol., Dalian Univ. of Technol., Dalian, China
ABSTRACT
Protein complexes are important for unraveling the secrets of cellular organization and function. Many computational approaches have been developed to predict protein complexes in protein-protein interaction (PPI) networks. However, most existing approaches focus mainly on the topological structure of PPI networks, and largely ignore the gene ontology (GO) annotation information. In this paper, we constructed ontology attributed PPI networks with PPI data and GO resource. After constructing ontology attributed networks, we proposed a novel approach called CSO (clustering based on network structure and ontology attribute similarity). Structural information and GO attribute information are complementary in ontology attributed networks. CSO can effectively take advantage of the correlation between frequent GO annotation sets and the dense subgraph for protein complex prediction. Our proposed CSO approach was applied to four different yeast PPI data sets and predicted many well-known protein complexes. The experimental results showed that CSO was valuable in predicting protein complexes and achieved state-of-the-art performance.
INDEX TERMS
Proteins, Ontologies, Prediction algorithms, Correlation, Bioinformatics, Computational biology,protein complex prediction, topology, cellular biophysics, proteins, proteomics, CSO approach, protein complex prediction, large ontology attributed protein-protein interaction networks, cellular organization, cellular function, PPI networks, topological structure, gene ontology, GO annotation information, Proteins, Ontologies, Prediction algorithms, Correlation, Bioinformatics, Computational biology, protein-protein interaction, Clustering, gene ontology
CITATION
Yijia Zhang, Hongfei Lin, Zhihao Yang, Jian Wang, Yanpeng Li, Bo Xu, "Protein Complex Prediction in Large Ontology Attributed Protein-Protein Interaction Networks", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.10, no. 3, pp. 729-741, May-June 2013, doi:10.1109/TCBB.2013.86
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