title: LocTree2 predicts localization for all domains of life.
abstract: BACKGROUND
  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.
  
  
  BACKGROUND
  Online through PredictProtein (predictprotein.org); as standalone version at http://www.rostlab.org/services/loctree2.
  
  
  BACKGROUND
  localization@rostlab.org
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: TUM, Bioinformatik-I12, Informatik, Boltzmannstrasse 3, Garching 85748, Germany. localization@rostlab.org
authors.forename: Tatyana
authors.initials: T
authors.lastname: Goldberg
authors.forename: Tobias
authors.initials: T
authors.lastname: Hamp
authors.forename: Burkhard
authors.initials: B
authors.lastname: Rost
mesh_terms: D000818:Animals; D019843:Archaeal Proteins / Q000032:analysis*; D001426:Bacterial Proteins / Q000032:analysis*; D008565:Membrane Proteins / Q000032:analysis*; D058977:Molecular Sequence Annotation; D011506:Proteins / Q000032:analysis*; D020539:Sequence Analysis, Protein; D060388:Support Vector Machine
chemical_list: D019843:Archaeal Proteins; D001426:Bacterial Proteins; D008565:Membrane Proteins; D011506:Proteins