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Bioinformatics Advance Access published online on March 28, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm115
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© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

SherLoc : High-Accuracy Prediction of Protein Subcellular Localization by Integrating Text and Protein Sequence Data

Hagit Shatkay a,*, Annette Höglund b, Scott Brady a, Torsten Blum b, Pierre Dönnes b and Oliver Kohlbacher b

aSchool of Computing, Queen’s University, Kingston, Ontario, Canada
bDiv. for Simulation of Biological Systems, ZBIT/WSI, University of Tübingen, Germany

*To whom correspondence should be addressed. Hagit Shatkay, E-mail: shatkay{at}cs.queensu.ca


  Abstract

Motivation: Knowing the localization of a protein within the cell helps elucidate its role in biological processes, its function, and its potential as a drug target. Thus, subcellular localization prediction is an active research area. Numerous localization prediction systems are described in the literature; some focus on specific localizations or organisms, while others attempt to cover a wide range of localizations.

Results: We introduce SherLoc, a new comprehensive system for predicting the localization of eukaryotic proteins. It integrates several types of sequence and text-based features. While applying the widelyused support vector machines (SVMs), SherLoc’s main novelty lies in the way in which it selects its text sources and features, and integrates those with sequence-based features. We test SherLoc on previously used datasets, as well as on a new set devised specifically to test its predictive power, and show that SherLoc consistently improves on previous reported results. We also report the results of applying SherLoc to a large set of yet-unlocalized proteins.

Availability: SherLoc, along with supplementary information, is available at: http://www-bs.informatik.uni-tuebingen.de/Services/SherLoc/.

Associate Editor: Prof. Alfonso Valencia

Received on September 11, 2006; revised on March 17, 2007; accepted on March 17, 2007

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