title: Prediction of protein B-factors using multi-class bounded SVM.
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.
authors.affiliation: Intelligent Computing Lab, Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei Anhui, 230031, China.
authors.forename: Peng
authors.initials: P
authors.lastname: Chen
authors.forename: Bing
authors.initials: B
authors.lastname: Wang
authors.forename: Hau-San
authors.initials: HS
authors.lastname: Wong
authors.forename: De-Shuang
authors.initials: DS
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D019295:Computational Biology; D030562:Databases, Protein; D057927:Hydrophobic and Hydrophilic Interactions; D008958:Models, Molecular; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins