@article{Hoeglund2006,
title = {MultiLoc: prediction of protein subcellular localization using N-terminal
targeting sequences, sequence motifs and amino acid composition.},
author = {Annette H\"oglund and Pierre D\"onnes and Torsten Blum and Hans-Werner Adolph and Oliver Kohlbacher},
journal = {Bioinformatics},
month = {May},
number = {10},
pages = {1158--1165},
url = {http://dx.doi.org/10.1093/bioinformatics/btl002},
volume = {22},
year = {2006},
abstract = {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: \url{http://www-bs.informatik.uni-tuebingen.de/Services/MultiLoc/}},
pmid = {16428265}, timestamp = {2007.05.18}, pii = {btl002}, owner = {Marco},
keywords = {SubCellLoc }
}
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