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A novel protein complex identification algorithm based on connected affinity clique extension (CACE)

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成果类型:
期刊论文
作者:
Li, Peng*;He, Tingting(何婷婷);Hu, Xiaohua;Zhao, Junmin;Shen, Xianjun;...
通讯作者:
Li, Peng
作者机构:
[He, Tingting; Shen, Xianjun; Hu, Xiaohua; Li, Peng; Zhang, Ming; Wang, Yan] Cent China Normal Univ, Sch Comp, Wuhan 430079, Peoples R China.
[Zhao, Junmin] Henan Univ Urban Construct, Pingdingshan 467036, Peoples R China.
通讯机构:
[Li, Peng] C
Cent China Normal Univ, Sch Comp, Wuhan 430079, Peoples R China.
语种:
英文
关键词:
Algorithm CACE;connected affinity;effective and accurately;overlapping functional modules
期刊:
IEEE Transactions on NanoBioscience
ISSN:
1536-1241
年:
2014
卷:
13
期:
2
页码:
89-96
基金类别:
NSF of ChinaNational Natural Science Foundation of China (NSFC) [90920005, 61003192]; Major Project of State Language Commission in the Twelfth Five-year Plan Period [ZDI125-1]; Project in the National Science & Technology Pillar Program in the Twelfth Five-year Plan Period [2012BAK24B01]; Program of Introducing Talents of Discipline to UniversitiesMinistry of Education, China - 111 Project [B07042]; NSF of Hubei Province [2011CDA034]; self-determined research Funds of CCNU from the colleges' basic research and operation of MOE [CCNU10A02009, CCNU10C01005]
机构署名:
本校为第一且通讯机构
院系归属:
计算机学院
国家数字化学习工程技术研究中心
摘要:
A novel algorithm based on Connected Affinity Clique Extension (CACE) for mining overlapping functional modules in protein interaction network is proposed in this paper. In this approach, the value of protein connected affinity which is inferred from protein complexes is interpreted as the reliability and possibility of interaction. The protein interaction network is constructed as a weighted graph, and the weight is dependent on the connected affinity coefficient. The experimental results of our CACE in two test data sets show that the CACE can detect the functional modules much more effectiv...

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