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

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

doi:10.2174/092986607779816078

ISSN: 0929-8665
E-ISSN: 1875-5305

Prediction of Protein B-Factors Using Multi-Class Bounded SVM
Authors: Peng Chen¹, Bing Wang², Hau-San Wong³ and De-Shuang Huang⁴
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¹ Intelligent Computing Lab,Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei Anhui, 230031, China. ² Intelligent Computing Lab,Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei Anhui, 230031, China. ³ Intelligent Computing Lab,Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei Anhui, 230031, China. ⁴ Intelligent Computing Lab,Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei Anhui, 230031, China.
Source: Protein and Peptide Letters, Volume 14, Issue 2, Feb 2007, p. 185 - 190
DOI: https://doi.org/10.2174/092986607779816078
- Available online: 01 Feb 2007

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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2007-02-01

2025-05-22

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Article Type: Research Article

Keyword(s): B-factors; Bounded Support Vector Machine; Evolutionary rate; Hydrophobicity profile; Sequence profile

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

Abstract

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