NDLI: Applying fuzzy support vector machine to predict membrane protein interactions with different representations

Content Provider	IEEE Xplore Digital Library
Author	Pei-Ying Zhao Yong-Sheng Ding
Copyright Year	2009
Description	Author affiliation: College of Information Sciences and Technolog, Donghua University, Shanghai, China (Pei-Ying Zhao; Yong-Sheng Ding)
Abstract	Membrane protein interactions are involved in the regulation and execution of all biochemical pathways within the cell. It is crucial to identify the binding partners for understanding the function of an uncharacterized protein, and when these partners turn out to have known function, deductions about the potential role of the uncharacterized protein can often be made. However, the analysis of interactions between membrane proteins is difficult because of the hydrophobic nature of these proteins, and conventional biochemical and genetic assays are often of limited use. In this paper, a novel method is presented for the prediction of membrane protein interactions representing the interactions with different features. We adopt fuzzy support vector machine as our classifier. Jackknife tests on the working datasets indicate that the precision, sensitivity and accuracy are improved greatly. The results show that the proposed method is efficient to genetically predict membrane protein interactions.
Starting Page	193
Ending Page	196
File Size	638827
Page Count	4
File Format	PDF
ISBN	9781424442478
DOI	10.1109/CCCM.2009.5267778
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-08
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Protein engineering Genomics Educational technology interactions of membrane protei Support vector machines Fungi fuzzy support vector machine membrane proteins Textile technology Genetics Biomembranes Large-scale systems Bioinformatics
Content Type	Text
Resource Type	Article

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