BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis

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dc.citation.articleNumbere1006650en_US
dc.citation.issueNumber4en_US
dc.citation.journalTitlePLoS Computational Biologyen_US
dc.citation.volumeNumber15en_US
dc.contributor.authorBouckaert, Remcoen_US
dc.contributor.authorVaughan, Timothy G.en_US
dc.contributor.authorBarido-Sottani, Joëlleen_US
dc.contributor.authorDuchêne, Sebastiánen_US
dc.contributor.authorFourment, Mathieuen_US
dc.contributor.authorGavryushkina, Alexandraen_US
dc.contributor.authorHeled, Josephen_US
dc.contributor.authorJones, Grahamen_US
dc.contributor.authorKühnert, Deniseen_US
dc.contributor.authorDe Maio, Nicolaen_US
dc.contributor.authorMatschiner, Michaelen_US
dc.contributor.authorMendes, Fábio K.en_US
dc.contributor.authorMüller, Nicola F.en_US
dc.contributor.authorOgilvie, Huw A.en_US
dc.contributor.authordu Plessis, Louisen_US
dc.contributor.authorPopinga, Alexen_US
dc.contributor.authorRambaut, Andrewen_US
dc.contributor.authorRasmussen, Daviden_US
dc.contributor.authorSiveroni, Igoren_US
dc.contributor.authorSuchard, Marc A.en_US
dc.contributor.authorWu, Chieh-Hisen_US
dc.contributor.authorXie, Dongen_US
dc.contributor.authorZhang, Chien_US
dc.contributor.authorStadler, Tanjaen_US
dc.contributor.authorDrummond, Alexei J.en_US
dc.date.accessioned2021-12-17T20:08:22Zen_US
dc.date.available2021-12-17T20:08:22Zen_US
dc.date.issued2019en_US
dc.description.abstractElaboration of Bayesian phylogenetic inference methods has continued at pace in recent years with major new advances in nearly all aspects of the joint modelling of evolutionary data. It is increasingly appreciated that some evolutionary questions can only be adequately answered by combining evidence from multiple independent sources of data, including genome sequences, sampling dates, phenotypic data, radiocarbon dates, fossil occurrences, and biogeographic range information among others. Including all relevant data into a single joint model is very challenging both conceptually and computationally. Advanced computational software packages that allow robust development of compatible (sub-)models which can be composed into a full model hierarchy have played a key role in these developments. Developing such software frameworks is increasingly a major scientific activity in its own right, and comes with specific challenges, from practical software design, development and engineering challenges to statistical and conceptual modelling challenges. BEAST 2 is one such computational software platform, and was first announced over 4 years ago. Here we describe a series of major new developments in the BEAST 2 core platform and model hierarchy that have occurred since the first release of the software, culminating in the recent 2.5 release.en_US
dc.identifier.citationBouckaert, Remco, Vaughan, Timothy G., Barido-Sottani, Joëlle, et al.. "BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis." <i>PLoS Computational Biology,</i> 15, no. 4 (2019) Public Library of Science: https://doi.org/10.1371/journal.pcbi.1006650.en_US
dc.identifier.digitaldocument-2en_US
dc.identifier.doihttps://doi.org/10.1371/journal.pcbi.1006650en_US
dc.identifier.urihttps://hdl.handle.net/1911/111878en_US
dc.language.isoengen_US
dc.publisherPublic Library of Scienceen_US
dc.rightsThis is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.titleBEAST 2.5: An advanced software platform for Bayesian evolutionary analysisen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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