Porter: a new, accurate server for protein secondary structure prediction
Citation:
Pollastri, G. and McLysaght, A., Porter: a new, accurate server for protein secondary structure prediction, Bioinformatics, 21, 8, 2005, 1719, 1720Download Item:
Abstract:
Porter is a new system for protein secondary structure prediction in three classes. Porter relies on bidirectional recurrent neural networks with shortcut connections, accurate coding of input profiles obtained from multiple sequence alignments, second stage filtering by recurrent neural networks, incorporation of long range information and large-scale ensembles of predictors. Porter's accuracy, tested by rigorous 5-fold cross-validation on a large set of proteins, exceeds 79%, significantly above a copy of the state-of-the-art SSpro server, better than any system published to date. AVAILABILITY: Porter is available as a public web server at http://distill.ucd.ie/porter/
Sponsor
Grant Number
Science Foundation Ireland
Author's Homepage:
http://people.tcd.ie/mclysagaDescription:
PUBLISHED
Author: MC LYSAGHT, AOIFE
Publisher:
Oxford University PressType of material:
Journal ArticleCollections
Series/Report no:
Bioinformatics;21;
8;
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Full text availableKeywords:
GeneticsMetadata
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