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Updated: Sep 30, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
Artificial neural network method for predicting protein secondary structure content
Yu-Dong Cai1, Xiao-Jun Liu, Xue-Biao Xu
1Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences. y.cai@umist.ac.uk
Abstract:
In this paper, the neural network method was applied to predict the content of protein secondary structure elements that was based on 'pair-coupled amino acid composition', in which the sequence coupling effects are explicitly included through a series of conditional probability elements. The prediction was examined by a self-consistency test and an independent-dataset. Both indicated good results obtained when using the neural network method to predict the contents of alpha-helix, beta-sheet, parallel beta-sheet strand, antiparallel beta-sheet strand, beta-bridge, 3(10)-helix, pi-helix, H-bonded turn, bend, and random coil.
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