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dc.contributor.authorKoslovsky, Matthew D.
Vannucci, Marina
dc.date.accessioned 2020-08-14T20:13:37Z
dc.date.available 2020-08-14T20:13:37Z
dc.date.issued 2020
dc.identifier.citation Koslovsky, Matthew D. and Vannucci, Marina. "MicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R package." BMC Bioinformatics, 21, no. 1 (2020) Springer Nature: https://doi.org/10.1186/s12859-020-03640-0.
dc.identifier.urihttps://hdl.handle.net/1911/109220
dc.description.abstract Understanding the relation between the human microbiome and modulating factors, such as diet, may help researchers design intervention strategies that promote and maintain healthy microbial communities. Numerous analytical tools are available to help identify these relations, oftentimes via automated variable selection methods. However, available tools frequently ignore evolutionary relations among microbial taxa, potential relations between modulating factors, as well as model selection uncertainty.
dc.language.iso eng
dc.publisher Springer Nature
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.title MicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R package
dc.type Journal article
dc.citation.journalTitle BMC Bioinformatics
dc.citation.volumeNumber 21
dc.citation.issueNumber 1
dc.type.dcmi Text
dc.identifier.doihttps://doi.org/10.1186/s12859-020-03640-0
dc.type.publication publisher version
dc.citation.articleNumber 301


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