Bioinformatics Advance Access originally published online on January 20, 2006
Bioinformatics 2006 22(10):1158-1165; doi:10.1093/bioinformatics/btl002
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MultiLoc: prediction of protein subcellular localization using N-terminal targeting sequences, sequence motifs and amino acid composition
1 Division for Simulation of Biological Systems, WSI/ZBIT, Eberhard Karls University Tübingen Sand 14, D-72076 Tübingen, Germany
2 Department of Biochemistry and Center for Bioinformatics, Saarland University D-66041 Saarbrücken, Germany
*To whom correspondence should be addressed.
Motivation: Functional annotation of unknown proteins is a major goal in proteomics. A key annotation is the prediction of a protein's subcellular localization. Numerous prediction techniques have been developed, typically focusing on a single underlying biological aspect or predicting a subset of all possible localizations. An important step is taken towards emulating the protein sorting process by capturing and bringing together biologically relevant information, and addressing the clear need to improve prediction accuracy and localization coverage.
Results: Here we present a novel SVM-based approach for predicting subcellular localization, which integrates N-terminal targeting sequences, amino acid composition and protein sequence motifs. We show how this approach improves the prediction based on N-terminal targeting sequences, by comparing our method TargetLoc against existing methods. Furthermore, MultiLoc performs considerably better than comparable methods predicting all major eukaryotic subcellular localizations, and shows better or comparable results to methods that are specialized on fewer localizations or for one organism.
Availability: http://www-bs.informatik.uni-tuebingen.de/Services/MultiLoc/
Contact: hoeglund{at}informatik.uni-tuebingen.de
Received on November 10, 2005; revised on December 9, 2005; accepted on January 12, 2006
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