{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T02:24:52Z","timestamp":1773195892022,"version":"3.50.1"},"reference-count":16,"publisher":"Oxford University Press (OUP)","issue":"8","license":[{"start":{"date-parts":[[2017,1,21]],"date-time":"2017-01-21T00:00:00Z","timestamp":1484956800000},"content-version":"vor","delay-in-days":31,"URL":"https:\/\/academic.oup.com\/journals\/pages\/about_us\/legal\/notices"}],"funder":[{"DOI":"10.13039\/100011350","name":"MOSAIC","doi-asserted-by":"publisher","award":["600914"],"award-info":[{"award-number":["600914"]}],"id":[{"id":"10.13039\/100011350","id-type":"DOI","asserted-by":"publisher"}]},{"name":"COMEX"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,4,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>A Bayesian Network is a probabilistic graphical model that encodes probabilistic dependencies between a set of random variables. We introduce bnstruct, an open source R package to (i) learn the structure and the parameters of a Bayesian Network from data in the presence of missing values and (ii) perform reasoning and inference on the learned Bayesian Networks. To the best of our knowledge, there is no other open source software that provides methods for all of these tasks, particularly the manipulation of missing data, which is a common situation in practice.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and Implementation<\/jats:title><jats:p>The software is implemented in R and C and is available on CRAN under a GPL licence.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btw807","type":"journal-article","created":{"date-parts":[[2016,12,15]],"date-time":"2016-12-15T12:09:51Z","timestamp":1481803791000},"page":"1250-1252","source":"Crossref","is-referenced-by-count":83,"title":["bnstruct: an R package for Bayesian Network structure learning in the presence of missing data"],"prefix":"10.1093","volume":"33","author":[{"given":"Alberto","family":"Franzin","sequence":"first","affiliation":[{"name":"IRIDIA-CoDE, Universit\u00e9 Libre de Bruxelles, Brussels, Belgium"},{"name":"Department of Information Engineering, University of Padova, Padova, Italy"}]},{"given":"Francesco","family":"Sambo","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, University of Padova, Padova, Italy"}]},{"given":"Barbara","family":"Di Camillo","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, University of Padova, Padova, Italy"}]}],"member":"286","published-online":{"date-parts":[[2016,12,21]]},"reference":[{"key":"2023020205021718000_btw807-B1","first-page":"20","author":"Bottcher","year":"2013"},{"key":"2023020205021718000_btw807-B2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.2517-6161.1977.tb01600.x","article-title":"Maximum likelihood from incomplete data via the EM algorithm","volume":"39","author":"Dempster","year":"1977","journal-title":"J. R. Stat. Soc. Ser. B (Methodological)"},{"key":"2023020205021718000_btw807-B3","first-page":"902","volume-title":"Aaai\/Iaai","author":"Druzdzel","year":"1999"},{"key":"2023020205021718000_btw807-B4","first-page":"125","volume-title":"ICML","author":"Friedman","year":"1997"},{"key":"2023020205021718000_btw807-B5","first-page":"129","volume-title":"UAI-98","author":"Friedman","year":"1998"},{"key":"2023020205021718000_btw807-B6","first-page":"196","volume-title":"UAI-99","author":"Friedman","year":"1999"},{"key":"2023020205021718000_btw807-B7","volume-title":"Probabilistic Graphical Models: Principles and Techniques","author":"Koller","year":"2009"},{"key":"2023020205021718000_btw807-B8","doi-asserted-by":"crossref","first-page":"e1003676.","DOI":"10.1371\/journal.pcbi.1003676","article-title":"Cgbayesnets: conditional Gaussian Bayesian network learning and inference with mixed discrete and continuous data","volume":"10","author":"McGeachie","year":"2014","journal-title":"PLoS Comput. Biol"},{"key":"2023020205021718000_btw807-B9","first-page":"1024","article-title":"The Bayes net toolbox for MATLAB","volume":"33","author":"Murphy","year":"2001","journal-title":"Comput. Sci. Stat"},{"key":"2023020205021718000_btw807-B10","author":"P\u00e9rez-Bernab\u00e9","year":"2015"},{"key":"2023020205021718000_btw807-B11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v035.i03","article-title":"Learning Bayesian Networks with the bnlearn R Package","volume":"35","author":"Scutari","year":"2010","journal-title":"J. Stat. Softw"},{"key":"2023020205021718000_btw807-B12","first-page":"159","article-title":"Python environment for Bayesian learning: inferring the structure of Bayesian networks from knowledge and data","volume":"10","author":"Shah","year":"2009","journal-title":"J. Mach. Learn. Res. JMLR"},{"key":"2023020205021718000_btw807-B13","doi-asserted-by":"crossref","first-page":"2498","DOI":"10.1101\/gr.1239303","article-title":"Cytoscape: a software environment for integrated models of biomolecular interaction networks","volume":"13","author":"Shannon","year":"2003","journal-title":"Genome Res"},{"key":"2023020205021718000_btw807-B14","first-page":"445","volume-title":"UAI-06","author":"Silander","year":"2006"},{"key":"2023020205021718000_btw807-B15","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1056\/NEJM199309303291401","article-title":"The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus","volume":"329","author":"The DCCT Research Group","year":"1993","journal-title":"N. Engl. J. Med"},{"key":"2023020205021718000_btw807-B16","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1007\/s10994-006-6889-7","article-title":"The Max-Min Hill-Climbing Bayesian network structure learning algorithm","volume":"65","author":"Tsamardinos","year":"2006","journal-title":"Mach. Learn"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/33\/8\/1250\/49038616\/bioinformatics_33_8_1250.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/33\/8\/1250\/49038616\/bioinformatics_33_8_1250.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,21]],"date-time":"2024-06-21T06:31:30Z","timestamp":1718951490000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/33\/8\/1250\/2730229"}},"subtitle":[],"editor":[{"given":"Jonathan","family":"Wren","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2016,12,21]]},"references-count":16,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2017,4,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btw807","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2017,4,15]]},"published":{"date-parts":[[2016,12,21]]}}}