Dynamic metabolomic prediction based on genetic variation for Hordeum vulgare

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but.event.date26.04.2022cs
but.event.titleSTUDENT EEICT 2022cs
dc.contributor.authorNemčeková, P.
dc.contributor.authorSchwarzerová, J.
dc.date.accessioned2023-04-25T10:17:08Z
dc.date.available2023-04-25T10:17:08Z
dc.date.issued2022cs
dc.description.abstractHordeum vulgare, like many other crops, suffers from the reduction of genetic diversity caused by climate changes. Therefore, it is necessary to improve the performance of its breeding. Nowadays, the area of interest in current research focuses on indirect selection methods based on computational prediction modeling. This study deals with dynamic metabolomic prediction based on genomic data consisting of 33,005 single nucleotide polymorphisms. Metabolomic data include 128 metabolites belonging to 25 Halle exotic barley families. The main goal of this study is creating dynamic metabolomic predictions using different approaches chosen upon various publications. Our created models will be helpful for the prediction of phenotype or for revealing important traits of Hordeum vulgare.en
dc.formattextcs
dc.format.extent251-254cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings I of the 28st Conference STUDENT EEICT 2022: General papers. s. 251-254. ISBN 978-80-214-6029-4cs
dc.identifier.isbn978-80-214-6029-4
dc.identifier.urihttp://hdl.handle.net/11012/209339
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings I of the 28st Conference STUDENT EEICT 2022: General papersen
dc.relation.urihttps://conf.feec.vutbr.cz/eeict/index/pages/view/ke_stazenics
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectMachine learningen
dc.subjectSingle nucleotide polymorphismen
dc.subjectgenomic predictionen
dc.subjectHordeum vulgareen
dc.titleDynamic metabolomic prediction based on genetic variation for Hordeum vulgareen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
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