title: ProbOnto: ontology and knowledge base of probability distributions.
abstract: Probability distributions play a central role in mathematical and statistical modelling. The encoding, annotation and exchange of such models could be greatly simplified by a resource providing a common reference for the definition of probability distributions. Although some resources exist, no suitably detailed and complex ontology exists nor any database allowing programmatic access.
  
  
  
  ProbOnto, is an ontology-based knowledge base of probability distributions, featuring more than 80 uni- and multivariate distributions with their defining functions, characteristics, relationships and re-parameterization formulas. It can be used for model annotation and facilitates the encoding of distribution-based models, related functions and quantities.
  
  
  
  http://probonto.org
  
  
  
  mjswat@ebi.ac.uk
  
  
  
  Supplementary data are available at Bioinformatics online.
authors.affiliation: EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK.
authors.forename: Maciej J
authors.initials: MJ
authors.lastname: Swat
authors.affiliation: CHIME, University College London, London, UK.
authors.forename: Pierre
authors.initials: P
authors.lastname: Grenon
authors.affiliation: EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK.
authors.forename: Sarala
authors.initials: S
authors.lastname: Wimalaratne
mesh_terms: D019295:Computational Biology; D016208:Databases, Factual; D051188:Knowledge Bases; D011336:Probability