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dc.contributor.authorVidela Rodriguez, Emiliano Ariel
dc.contributor.authorMitchell, John B. O.
dc.contributor.authorSmith, V. Anne
dc.identifier.citationVidela Rodriguez , E A , Mitchell , J B O & Smith , V A 2022 , ' A Bayesian network structure learning approach to identify genes associated with stress in spleens of chickens ' , Scientific Reports , vol. 12 , 7482 .
dc.identifier.otherPURE: 279304183
dc.identifier.otherPURE UUID: 483a2d97-44c5-4cad-8951-edf01edde10a
dc.identifier.otherORCID: /0000-0002-0379-6097/work/113060866
dc.identifier.otherORCID: /0000-0002-0487-2469/work/113060904
dc.identifier.otherScopus: 85129722747
dc.identifier.otherWOS: 000791825700030
dc.descriptionThis work was supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 812777en
dc.description.abstractDifferences in the expression patterns of genes have been used to measure the effects of non-stress or stress conditions in poultry species. However, the list of genes identified can be extensive and they might be related to several biological systems. Therefore, the aim of this study was to identify a small set of genes closely associated with stress in a poultry animal model, the chicken (Gallus gallus), by reusing and combining data previously published together with bioinformatic analysis and Bayesian networks in a multi-step approach. Two datasets were collected from publicly available repositories and pre-processed. Bioinformatics analyses were performed to identify genes common to both datasets that showed differential expression patterns between non-stress and stress conditions. Bayesian networks were learnt using a Simulated Annealing algorithm implemented in the software Banjo. The structure of the Bayesian network consisted of 16 out of 19 genes together with the stress condition. Network structure showed CARD19 directly connected to the stress condition plus highlighted CYGB, BRAT1, and EPN3 as relevant, suggesting these genes could play a role in stress. The biological functionality of these genes is related to damage, apoptosis, and oxygen provision, and they could potentially be further explored as biomarkers of stress.
dc.relation.ispartofScientific Reportsen
dc.rightsCopyright © The Author(s) 2022. This 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
dc.subjectBayesian networken
dc.subjectMarkov Blanketen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectQH301 Biologyen
dc.subjectSF Animal cultureen
dc.titleA Bayesian network structure learning approach to identify genes associated with stress in spleens of chickensen
dc.typeJournal articleen
dc.contributor.sponsorEuropean Commissionen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. EaSTCHEMen
dc.contributor.institutionUniversity of St Andrews. Biomedical Sciences Research Complexen
dc.contributor.institutionUniversity of St Andrews. School of Chemistryen
dc.contributor.institutionUniversity of St Andrews. St Andrews Bioinformatics Uniten
dc.contributor.institutionUniversity of St Andrews. Office of the Principalen
dc.contributor.institutionUniversity of St Andrews. St Andrews Centre for Exoplanet Scienceen
dc.contributor.institutionUniversity of St Andrews. Centre for Biological Diversityen
dc.contributor.institutionUniversity of St Andrews. Centre for Higher Education Researchen
dc.contributor.institutionUniversity of St Andrews. Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews. Institute of Behavioural and Neural Sciencesen
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
dc.description.statusPeer revieweden

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