Support vector machines for prediction of protein domain structural class.
The support vector machines (SVMs) method was introduced for predicting the structural class of protein domains. The results obtained through the self-consistency test, jack-knife test, and independent dataset test have indicated that the current method and the elegant component-coupled algorithm developed by Chou and co-workers, if effectively complemented with each other, may become a powerful tool for predicting the structural class of protein domains.
Cai
Yu-Dong
YD
Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, Shanghai 200233, China. y.cai@umist.ac.uk
Liu
Xiao-Jun
XJ
Xu
Xue-Biao
XB
Chou
Kou-Chen
KC
D000465:Algorithms; D000596:Amino Acids / Q000032:analysis; D000818:Animals; D016208:Databases, Factual; D008956:Models, Chemical; D010363:Pattern Recognition, Automated; D017434:Protein Structure, Tertiary
D000596:Amino Acids