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Open Access

Mining Protein Complexes from PPI Networks Using the Minimum Vertex Cut

Xiaojun Ding1,2Weiping Wang1Xiaoqing Peng1Jianxin Wang1( )
School of Information Science and Engineering, Central South University, Changsha 410083, China
Department of Computer Science, Georgia State University, Atlanta, GA 30302, USA
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Abstract

Evidence shows that biological systems are composed of separable functional modules. Identifying protein complexes is essential for understanding the principles of cellular functions. Many methods have been proposed to mine protein complexes from protein-protein interaction networks. However, the performances of these algorithms are not good enough since the protein-protein interactions detected from experiments are not complete and have noise. This paper presents an analysis of the topological properties of protein complexes to show that although proteins from the same complex are more highly connected than proteins from different complexes, many protein complexes are not very dense (density ≥ 0.8). A method is then given to mine protein complexes that are relatively dense (density ≥ 0.4). In the first step, a topology property is used to identify proteins that are probably in a same complex. Then, a possible boundary is calculated based on a minimum vertex cut for the protein complex. The final complex is formed by the proteins within the boundary. The method is validated on a yeast protein-protein interaction network. The results show that this method has better performance in terms of sensitivity and specificity compared with other methods. The functional consistency is also good.

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Tsinghua Science and Technology
Pages 674-681

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Cite this article:
Ding X, Wang W, Peng X, et al. Mining Protein Complexes from PPI Networks Using the Minimum Vertex Cut. Tsinghua Science and Technology, 2012, 17(6): 674-681. https://doi.org/10.1109/TST.2012.6374369

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Received: 21 September 2012
Revised: 15 October 2012
Published: 05 December 2012
© The author(s) 2012.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).