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Bioinformatics Advance Access originally published online on May 3, 2008
Bioinformatics 2008 24(13):1503-1509; doi:10.1093/bioinformatics/btn218
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

A support vector machine model for the prediction of proteotypic peptides for accurate mass and time proteomics

Bobbie-Jo M. Webb-Robertson 1,*, William R. Cannon 1, Christopher S. Oehmen 1, Anuj R. Shah 2, Vidhya Gurumoorthi 3, Mary S. Lipton 4 and Katrina M. Waters 1

1Computational Biology & Bioinformatics, 2Scientific Data Management, 3Applied Computer Science and 4Biological Separations and Mass Spectrometry, Pacific Northwest National Laboratory

*To whom correspondence should be addressed.


  Abstract

Motivation: The standard approach to identifying peptides based on accurate mass and elution time (AMT) compares profiles obtained from a high resolution mass spectrometer to a database of peptides previously identified from tandem mass spectrometry (MS/MS) studies. It would be advantageous, with respect to both accuracy and cost, to only search for those peptides that are detectable by MS (proteotypic).

Results: We present a support vector machine (SVM) model that uses a simple descriptor space based on 35 properties of amino acid content, charge, hydrophilicity and polarity for the quantitative prediction of proteotypic peptides. Using three independently derived AMT databases (Shewanella oneidensis, Salmonella typhimurium, Yersinia pestis) for training and validation within and across species, the SVM resulted in an average accuracy measure of 0.8 with a SD of <0.025. Furthermore, we demonstrate that these results are achievable with a small set of 12 variables and can achieve high proteome coverage.

Availability: http://omics.pnl.gov/software/STEPP.php

Contact: bj{at}pnl.gov

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: John Quackenbush

Received on March 18, 2008; revised on April 18, 2008; accepted on April 29, 2008

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