Zheng, X.; Wu, L.; Ye, S.; Chen, R. Simplified Swarm Optimization-Based Function Module Detection in Protein–Protein Interaction Networks. Appl. Sci.2017, 7, 412.
Zheng, X.; Wu, L.; Ye, S.; Chen, R. Simplified Swarm Optimization-Based Function Module Detection in Protein–Protein Interaction Networks. Appl. Sci. 2017, 7, 412.
Zheng, X.; Wu, L.; Ye, S.; Chen, R. Simplified Swarm Optimization-Based Function Module Detection in Protein–Protein Interaction Networks. Appl. Sci.2017, 7, 412.
Zheng, X.; Wu, L.; Ye, S.; Chen, R. Simplified Swarm Optimization-Based Function Module Detection in Protein–Protein Interaction Networks. Appl. Sci. 2017, 7, 412.
Abstract
Proteomics research has become one of the most important topics in the fields of life science and natural science. At present, research on protein–protein interaction networks (PPINs) mainly focuses on detecting protein complexes or function modules. However, existing approaches are either ineffective or incomplete. In this paper, we investigate function module detection mechanisms in PPIN, including open databases, existing detection algorithms and recent solutions. After that, we describe the proposed solution based on simplified swarm optimization (SSO) algorithm and gene ontology knowledge. The proposed solution implements SSO algorithm for clustering proteins with similar function, and imports biological gene ontology knowledge for further identifying function complexes and improving detection accuracy. Furthermore, we use four different categories of species dataset for experiment: Fruitfly, Mouse, Scere, and Human. The testing and analysis result show that the proposed solution is feasible, efficient and could achieve a higher accuracy of prediction than existing approaches.
Keywords
protein–protein interaction networks; protein function module; simplified swarm optimization
Subject
Computer Science and Mathematics, Information Systems
Copyright:
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