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BioMed Research International
Volume 2014, Article ID 720960, 9 pages
Research Article

A Least Square Method Based Model for Identifying Protein Complexes in Protein-Protein Interaction Network

1School of Computer Science and Technology, Harbin Institute of Technology, P.O. Box 319, 92 Xidazhi Street, Harbin 150001, China
2School of Information and Computer Engineering, Northeast Forestry University, Harbin 150040, China

Received 22 July 2014; Accepted 27 August 2014; Published 23 October 2014

Academic Editor: Yudong Cai

Copyright © 2014 Qiguo Dai et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Protein complex formed by a group of physical interacting proteins plays a crucial role in cell activities. Great effort has been made to computationally identify protein complexes from protein-protein interaction (PPI) network. However, the accuracy of the prediction is still far from being satisfactory, because the topological structures of protein complexes in the PPI network are too complicated. This paper proposes a novel optimization framework to detect complexes from PPI network, named PLSMC. The method is on the basis of the fact that if two proteins are in a common complex, they are likely to be interacting. PLSMC employs this relation to determine complexes by a penalized least squares method. PLSMC is applied to several public yeast PPI networks, and compared with several state-of-the-art methods. The results indicate that PLSMC outperforms other methods. In particular, complexes predicted by PLSMC can match known complexes with a higher accuracy than other methods. Furthermore, the predicted complexes have high functional homogeneity.