Improving the accuracy of protein secondary structure prediction using structural alignment |
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Authors: | Scott Montgomerie Shan Sundararaj Warren J Gallin David S Wishart |
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Affiliation: | (1) Department of Computing Science, University of Alberta, Edmonton, AB, T6G 2E8, Canada;(2) Department of Biological Sciences, University of Alberta, Edmonton, AB, T6G 2E9, Canada |
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Abstract: | Background The accuracy of protein secondary structure prediction has steadily improved over the past 30 years. Now many secondary structure prediction methods routinely achieve an accuracy (Q3) of about 75%. We believe this accuracy could be further improved by including structure (as opposed to sequence) database comparisons as part of the prediction process. Indeed, given the large size of the Protein Data Bank (>35,000 sequences), the probability of a newly identified sequence having a structural homologue is actually quite high. |
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