ProbOnto: ontology and knowledge base of probability distributions
2016
Motivation: 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.
Results: 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.
Availability and Implementation: http://probonto.org
Contact: ku.ca.ibe@tawsjm
Supplementary information: Supplementary data are available at Bioinformatics online.
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