Prediction of β-turns using double BP network with novel coding schemes of amino acids

Protein structure prediction is one of the most important problems in structural biology. β-turns are always at the turn of a protein tertiary structure and thus β-turn’s prediction is a key step in tertiary structure prediction. There are some methods to predict β-turns based on machine learning techniques such as k-nearest method, neural networks and support vector machine. In this paper, we construct a classifier using double BP networks and put forward two novel methods to code amino acids in the second network. When trained and tested on different datasets, they achieve more accuracy than other coding methods.

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