Document Detail


Feed-forward neural networks for secondary structure prediction.
MedLine Citation:
PMID:  7577845     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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.
Authors:
T W Barlow
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Journal of molecular graphics     Volume:  13     ISSN:  0263-7855     ISO Abbreviation:  J Mol Graph     Publication Date:  1995 Jun 
Date Detail:
Created Date:  1995-12-28     Completed Date:  1995-12-28     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  9014762     Medline TA:  J Mol Graph     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  175-83     Citation Subset:  IM    
Affiliation:
Physical Chemistry Laboratory, Oxford, England.
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MeSH Terms
Descriptor/Qualifier:
Neural Networks (Computer)*
Protein Structure, Secondary*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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