Prediction of protein secondary structure content by artificial neural network
暂无分享,去创建一个
The neural network method was applied to the prediction of the content of protein secondary structure elements, including α‐helix, β‐strand, β‐bridge, 310‐helix, π‐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. © 2003 Wiley Periodicals, Inc. J Comput Chem 24: 727–731, 2003
[1] G. Fasman. Prediction of Protein Structure and the Principles of Protein Conformation , 2012, Springer US.