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Algorithm Research & Explore
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390-397,420

Mining protein complexes based on ant colony clustering in dynamic weighted PPI network

Hu Jiana
Zhu Haiwanb
Mao Yiminb
a. Dept. of Information Engineering, College of Applied Science, b. School of Information Engineering, Jiangxi University of Science & Technology, Ganzhou Jiangxi 341000, China

Abstract

Since static PPI network are difficult to truly reflect the dynamic character of cells, the convergence speed is slow, cluster precision and recall is low in mining protein complex based on ant colony clustering, this paper proposed an ant colony clustering algorithm based on fuzzy granular and closeness degree to mine protein complexes in dynamic weighted PPI network, named FGCDACC-DPC(joint fuzzy granular and closeness degree ant colony clustering-DPC). First, based on the topological and biological characteristics of the PPI network, it designed a comprehensive weight metric(CWM) to accurately describe the interaction between proteins. Second, this method constructed a series of dense and highly co-expressed complex core based on the basic characteristic of the complexes, then it employed the picking and dropping operations, which based on fuzzy granular and closeness degree, to cluster the nodes in PPI network, in order to reduce effectively the computational complexity and randomness, speed up the clustering speed. Finally, this algorithm designed a local and global strategy founded on function transmission and timing functional relevance theory for weight's update, which achieved the function transmission between different generations of ant colonies and networks at different times to effectively improve clustering accuracy. FGCDACC-DPC algorithm was used to mine protein complexes on DIP data. Experimental results demonstrate that this algorithm has better performance on precision and recall, which is more reasonable to identify protein complexes.

Foundation Support

国家自然科学基金资助项目(41562019,41530640)
江西省自然基金资助项目(20161BAB203093,GJJ161566)
江西省教育厅科技项目(GJJ151528GJJ151531)
省社科规划项目(13YD020)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.07.0518
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 2
Section: Algorithm Research & Explore
Pages: 390-397,420
Serial Number: 1001-3695(2020)02-015-0390-08

Publish History

[2020-02-05] Printed Article

Cite This Article

胡健, 朱海湾, 毛伊敏. 基于蚁群聚类的动态加权PPI网络复合物挖掘 [J]. 计算机应用研究, 2020, 37 (2): 390-397,420. (Hu Jian, Zhu Haiwan, Mao Yimin. Mining protein complexes based on ant colony clustering in dynamic weighted PPI network [J]. Application Research of Computers, 2020, 37 (2): 390-397,420. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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