Literature DB >> 15359424

Reduced bio-basis function neural networks for protease cleavage site prediction.

Zheng Rong Yang1, Emily A Berry.   

Abstract

This paper presents a new neural learning algorithm for protease cleavage site prediction. The basic idea is to replace the radial basis function used in radial basis function neural networks by a so-called bio-basis function using amino acid similarity matrices. Mutual information is used to select bio-bases and a corresponding selection algorithm is developed. The algorithm has been applied to the prediction of HIV and Hepatitis C virus protease cleavage sites in proteins with success.

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Year:  2004        PMID: 15359424     DOI: 10.1142/s0219720004000715

Source DB:  PubMed          Journal:  J Bioinform Comput Biol        ISSN: 0219-7200            Impact factor:   1.122


  3 in total

1.  Mining SARS-CoV protease cleavage data using non-orthogonal decision trees: a novel method for decisive template selection.

Authors:  Zheng Rong Yang
Journal:  Bioinformatics       Date:  2005-03-29       Impact factor: 6.937

Review 2.  Peptide bioinformatics: peptide classification using peptide machines.

Authors:  Zheng Rong Yang
Journal:  Methods Mol Biol       Date:  2008

3.  Predicting proteolytic sites in extracellular proteins: only halfway there.

Authors:  Yossef Kliger; Eyal Gofer; Assaf Wool; Amir Toporik; Avihay Apatoff; Moshe Olshansky
Journal:  Bioinformatics       Date:  2008-03-04       Impact factor: 6.937

  3 in total

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