Journal
PROTEIN AND PEPTIDE LETTERS
Volume 13, Issue 10, Pages 985-991Publisher
BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/092986606778777551
Keywords
protein secondary structure prediction; two-level network; reliability score; naive bayes; semi-probability profile; multiple sequence alignment
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In this paper(1) we present a novel framework for protein secondary structure prediction. In this prediction framework, firstly we propose a novel parameterized semi-probability profile, which combines single sequence with evolutionary information effectively. Secondly, different semi-probability profiles are respectively applied as network input to predict protein secondary structure. Then a comparison among these different predictions is discussed in this article. Finally, naive Bayes approaches are used to combine these predictions in order to obtain a better prediction performance than individual prediction. The experimental results show that our proposed framework can indeed improve the prediction accuracy.
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