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author:

Zheng, K.L.X. (Zheng, K.L.X..) [1] | Rong, C. (Rong, C..) [2] | Yu, Y. (Yu, Y..) [3] | Chen, R. (Chen, R..) [4]

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Abstract:

With the completion of the Human Genome Project, proteomics research has become one of the most important topics in the fields of life science and natural science. The project determined that proteins participate in life activities mainly in the form of complexes. At present, research on protein-protein interaction networks (PPINs) have mainly focused on detecting protein complexes or function modules. This problem has been transformed into a recognizable dense subgraph problem in a PPIN diagram.The situation in PPIN research in recent years is introduced in this study, including commonly used databases, traditional detection algorithms, recent solutions, and the application of the swarm intelligence algorithms in this field. We then propose a detection scheme based on particle swarm optimization (PSO) and gene ontology knowledge. This scheme combines PSO and biological gene ontology knowledge to identify complexes from PPINs. Simultaneously, network topology knowledge improves the detection accuracy of the protein module. © 2016 IEEE.

Keyword:

Machine learning; Particle swarm optimization; Protein function module; Protein-protein interaction networks

Community:

  • [ 1 ] [Zheng, K.L.X.]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China
  • [ 2 ] [Rong, C.]Department of Computer Science and Electronic Engineering, University of Stavanger, Stavanger, Norway
  • [ 3 ] [Yu, Y.]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China
  • [ 4 ] [Chen, R.]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China

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Source :

Proceedings - 15th International Symposium on Parallel and Distributed Computing, ISPDC 2016

Year: 2017

Page: 327-333

Language: English

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SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 0

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