Journal
JOURNAL OF PROTEOME RESEARCH
Volume 8, Issue 11, Pages 5363-5366Publisher
AMER CHEMICAL SOC
DOI: 10.1021/pr900665y
Keywords
protein subcellular localization prediction; machine learning; text mining; Gene Ontology
Categories
Funding
- LGFG Promotionsverbund Pflanzliche Sensorhistidinkinasen
- NSERC [298292-04]
- CFI [10437]
- Ontario Early Researcher Award [ER07-04-085]
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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-bsinformatik.uni-tuebingen.de/Services/SherLoc2.
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