SherLoc2: A High-Accuracy Hybrid Method for Predicting Subcellular Localization of Proteins

SherLoc2 is a comprehensive high-accuracy subcellular localization prediction system. It is applicable to animal, fungal, and plant proteins and covers all main eukaryotic subcellular locations. SherLoc2 integrates several sequence-based features as well as text-based features. In addition, we incor...

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Bibliographic Details
Published inJournal of proteome research Vol. 8; no. 11; pp. 5363 - 5366
Main Authors Briesemeister, Sebastian, Blum, Torsten, Brady, Scott, Lam, Yin, Kohlbacher, Oliver, Shatkay, Hagit
Format Journal Article
LanguageEnglish
Published United States American Chemical Society 06.11.2009
Subjects
Animals
Fungal Proteins - analysis
Fungal Proteins - classification
Phylogeny
Plant Proteins - analysis
Plant Proteins - classification
Proteins - analysis
Proteins - classification
Reproducibility of Results
Software
Subcellular Fractions - chemistry
protein subcellular localization prediction
text mining
machine learning
Gene Ontology
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Summary:SherLoc2 is a comprehensive high-accuracy subcellular localization prediction system. It is applicable to animal, fungal, and plant proteins and covers all main eukaryotic subcellular locations. SherLoc2 integrates several sequence-based features as well as text-based features. In addition, we incorporate phylogenetic profiles and Gene Ontology (GO) terms derived from the protein sequence to considerably improve the prediction performance. SherLoc2 achieves an overall classification accuracy of up to 93% in 5-fold cross-validation. A novel feature, DiaLoc, allows users to manually provide their current background knowledge by describing a protein in a short abstract which is then used to improve the prediction. SherLoc2 is available both as a free Web service and as a stand-alone version at http://www-bs.informatik.uni-tuebingen.de/Services/SherLoc2.
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ISSN:1535-3893
1535-3907
DOI:10.1021/pr900665y