Journal
BMC GENOMICS
Volume 11, Issue -, Pages -Publisher
BMC
DOI: 10.1186/1471-2164-11-S3-S10
Keywords
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Funding
- National Natural Science Foundation of China [61003124, 60773111]
- National Basic Research 973 Program of China [2008CB317107]
- Ph.D. Programs Foundation of Ministry of Education of China [20090162120073]
- Central South University [201012200124]
- U.S. National Science Foundation [CCF-0514750, CCF-0646102, CNS-0831634]
- Program for Changjiang Scholars and Innovative Research Team in University [IRT0661]
- International Society of Intelligent Biological Medicine (ISIBM)
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The increasing availability of large-scale protein-protein interaction data has made it possible to understand the basic components and organization of cell machinery from the network level. The arising challenge is how to analyze such complex interacting data to reveal the principles of cellular organization, processes and functions. Many studies have shown that clustering protein interaction network is an effective approach for identifying protein complexes or functional modules, which has become a major research topic in systems biology. In this review, recent advances in clustering methods for protein interaction networks will be presented in detail. The predictions of protein functions and interactions based on modules will be covered. Finally, the performance of different clustering methods will be compared and the directions for future research will be discussed.
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