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http://dx.doi.org/10.3745/KIPSTB.2006.13B.7.679

Protein-Protein Interaction Reliability Enhancement System based on Feature Selection and Classification Technique  

Lee, Min-Su (이화여자대학교 컴퓨터학과)
Park, Seung-Soo (이화여자대학교 컴퓨터학과)
Lee, Sang-Ho (이화여자대학교 컴퓨터학과)
Yong, Hwan-Seung (이화여자대학교 컴퓨터학과)
Kang, Sung-Hee (명지대학교 방목기초교육대학)
Publication Information
The KIPS Transactions:PartB / v.13B, no.7, 2006 , pp. 679-688 More about this Journal
Abstract
Protein-protein interaction data obtained from high-throughput experiments includes high false positives. In this paper, we introduce a new protein-protein interaction reliability verification system. The proposed system integrates various biological features related with protein-protein interactions, and then selects the most relevant and informative features among them using a feature selection method. To assess the reliability of each protein-protein interaction data, the system construct a classifier that can distinguish true interacting protein pairs from noisy protein-protein interaction data based on the selected biological evidences using a classification technique. Since the performance of feature selection methods and classification techniques depends heavily upon characteristics of data, we performed rigorous comparative analysis of various feature selection methods and classification techniques to obtain optimal performance of our system. Experimental results show that the combination of feature selection method and classification algorithms provide very powerful tools in distinguishing true interacting protein pairs from noisy protein-protein interaction dataset. Also, we investigated the effects on performances of feature selection methods and classification techniques in the proposed protein interaction verification system.
Keywords
Data Mining; Classification Technique; Feature Selection; Protein-Protein Interaction;
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