Prediction of protein secondary structure content by artificial neural network.
The neural network method was applied to the prediction of the content of protein secondary structure elements, including alpha-helix, beta-strand, beta-bridge, 3(10)-helix, pi-helix, H-bonded turn, bend, and random coil. The "pair-coupled amino acid composition" originally proposed by K. C. Chou [J Protein Chem 1999, 18, 473] was adopted as the input. Self-consistency and independent-dataset tests were used to appraise the performance of the neural network. Results of both tests indicated high performance of the method.
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
Chou
Kuo-Chen
KC
D000465:Algorithms; D000596:Amino Acids / Q000737:chemistry*; D008958:Models, Molecular; D016571:Neural Networks, Computer; D017433:Protein Structure, Secondary
D000596:Amino Acids