Detecting and Sorting Targeting Peptides with Neural Networks and

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Detecting and Sorting Targeting Peptides with Neural Networks and

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by Support Vector Machines , John Hawkins , Mikael Bodén

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7 - 0 self

BibTeX

@MISC{Machines_detectingand,
    author = {Support Vector Machines and John Hawkins and Mikael Bodén},
    title = {Detecting and Sorting Targeting Peptides with Neural Networks and},
    year = {}
}

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Abstract

This paper presents a composite multi-layer classifier system for predicting the subcellular localization of proteins based on their amino acid sequence. The work is an extension of our previous predictor PProwler v1.1 which is itself built upon the series of predictors SignalP and TargetP. In this study we outline experiments conducted to improve the classifier design. The major improvement came from using Support Vector machines as a 'smart gate' sorting the outputs of several di#erent targeting peptide detection networks

Keyphrases

neural network predictor signalp support vector machine previous predictor pprowler v1 smart gate subcellular localization peptide detection network classifier design amino acid sequence composite multi-layer classifier system major improvement

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