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10.1093/bioinformatics/btw170 http://scihub22266oqcxt.onion/10.1093/bioinformatics/btw170 C5013898!5013898!27153608     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Bioinformatics 2016 ; 32 (17): 2719-21 Nephropedia Template TP {{tp|p=27153608|t=2016. ProbOnto: ontology and knowledge base of probability distributions |pdf=|usr=}}{{27153608}} gab.com Text ProbOnto: ontology and knowledge base of probability distributions JO: Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=27153608 #FOAvip 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.orgContact:mjswat@ebi.ac.ukSupplementary information:Supplementary data are available at Bioinformatics online. Twit Text FOAVip ProbOnto: ontology and knowledge base of probability distributions ????Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=27153608 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27153608 #FOAvip English Wikipedia <ref>{{Cite pmid|27153608}}</ref> ProbOnto: ontology and knowledge base of probability distributions #MMPMID27153608 Swat MJ; Grenon P; Wimalaratne S Bioinformatics 2016[Sep]; 32 (17): 2719-21 PMID27153608show ga 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.orgContact:mjswat@ebi.ac.ukSupplementary information:Supplementary data are available at Bioinformatics online. äProbOnto: ontology and knowledge base of probability distributions (epmc).pdf DeepDyve Pubget Overpricing