LocTree2 predicts localization for all domains of life.

TitleLocTree2 predicts localization for all domains of life.
Publication TypeJournal Article
Year of Publication2012
AuthorsGoldberg, T, Hamp, T, Rost, B
Date Published2012 Sep 15
KeywordsAnimals, Archaeal Proteins, Bacterial Proteins, Membrane Proteins, Molecular Sequence Annotation, Proteins, Sequence Analysis, Protein, Support Vector Machines

MOTIVATION: Subcellular localization is one aspect of protein function. Despite advances in high-throughput imaging, localization maps remain incomplete. Several methods accurately predict localization, but many challenges remain to be tackled.RESULTS: In this study, we introduced a framework to predict localization in life's three domains, including globular and membrane proteins (3 classes for archaea; 6 for bacteria and 18 for eukaryota). The resulting method, LocTree2, works well even for protein fragments. It uses a hierarchical system of support vector machines that imitates the cascading mechanism of cellular sorting. The method reaches high levels of sustained performance (eukaryota: Q18=65%, bacteria: Q6=84%). LocTree2 also accurately distinguishes membrane and non-membrane proteins. In our hands, it compared favorably with top methods when tested on new data.AVAILABILITY: Online through PredictProtein (predictprotein.org); as standalone version at http://www.rostlab.org/services/loctree2.CONTACT: localization@rostlab.orgSUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Alternate JournalBioinformatics
PubMed ID22962467
PubMed Central IDPMC3436817