| Feed-forward neural networks for secondary structure prediction. | |
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MedLine Citation:
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PMID: 7577845 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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A feed-forward neural network has been employed for protein secondary structure prediction. Attempts were made to improve on previous prediction accuracies using a hierarchical mixture of experts (HME). In this method input data are clustered and used to train a series of different networks. Application of an HME to the prediction of protein secondary structure is shown to provide no advantages over a single network. We have also tried various new input representations, chosen to incorporate the effect of residues a long distance away in the one-dimensional amino acid chain. Prediction accuracy using these methods is comparable to that achieved by other neural networks. |
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Authors:
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T W Barlow |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: Journal of molecular graphics Volume: 13 ISSN: 0263-7855 ISO Abbreviation: J Mol Graph Publication Date: 1995 Jun |
Date Detail:
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Created Date: 1995-12-28 Completed Date: 1995-12-28 Revised Date: 2006-11-15 |
Medline Journal Info:
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Nlm Unique ID: 9014762 Medline TA: J Mol Graph Country: UNITED STATES |
Other Details:
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Languages: eng Pagination: 175-83 Citation Subset: IM |
Affiliation:
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Physical Chemistry Laboratory, Oxford, England. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Neural Networks (Computer)* Protein Structure, Secondary* |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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