title: Prediction of protein secondary structure content using support vector machine.
abstract: In this paper, the support vector machine was trained to grasp the relationship between the pair-coupled amino acid composition and the content of protein secondary structural elements, including alpha-helix, 3(10)-helix, pi-helix, beta-strand, beta-bridge, turn, bend and the rest random coil. Self-consistency and cross validation tests were made to assess the performance of our method. Results superior to or competitive with the popular theoretical and experimental methods have been obtained.
authors.affiliation: School of Chemistry and Chemical Engineering, Sun Yat-Sen University, Guangzhou 510275, People's Republic of China.
authors.forename: Chao
authors.initials: C
authors.lastname: Chen
authors.forename: Yuanxin
authors.initials: Y
authors.lastname: Tian
authors.forename: Xiaoyong
authors.initials: X
authors.lastname: Zou
authors.forename: Peixiang
authors.initials: P
authors.lastname: Cai
authors.forename: Jinyuan
authors.initials: J
authors.lastname: Mo