Prediction of Protein B-Factors Using Multi-Class Bounded SVM

Peng      Chen; Bing      Wang; Hau-San      Wong; De-Shuang      Huang

doi:10.2174/092986607779816078

Abstract

In this paper, we propose the adoption of the bounded support vector machine (BSVM) to predict the B-factors of residues based on a number of distinctive properties of residues. Due to the ability of multi-class classification of the BSVM, we can elaborately distinguish our targets and obtain relatively higher accuracy.

Keywords: B-factors, Bounded Support Vector Machine, Sequence profile, Evolutionary rate, Hydrophobicity profile

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Protein & Peptide Letters

Title: Prediction of Protein B-Factors Using Multi-Class Bounded SVM

Volume: 14 Issue: 2

Author(s): Peng Chen, Bing Wang, Hau-San Wong and De-Shuang Huang

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Keywords: B-factors, Bounded Support Vector Machine, Sequence profile, Evolutionary rate, Hydrophobicity profile

Abstract: In this paper, we propose the adoption of the bounded support vector machine (BSVM) to predict the B-factors of residues based on a number of distinctive properties of residues. Due to the ability of multi-class classification of the BSVM, we can elaborately distinguish our targets and obtain relatively higher accuracy.

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Chen Peng, Wang Bing, Wong Hau-San and Huang De-Shuang, Prediction of Protein B-Factors Using Multi-Class Bounded SVM, Protein & Peptide Letters 2007; 14 (2) . https://dx.doi.org/10.2174/092986607779816078