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NEMČEKOVÁ, P. SCHWARZEROVÁ, J.
Originální název
Dynamic metabolomic prediction based on genetic variation for Hordeum vulgare
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Hordeum 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.
Klíčová slova
Machine learning, Single nucleotide polymorphism, genomic prediction, Hordeum vulgare
Autoři
NEMČEKOVÁ, P.; SCHWARZEROVÁ, J.
Vydáno
26. 4. 2022
Nakladatel
Brno University of Technology, Faculty of Electrical Engineering and Communication
Místo
Brno
ISBN
978-80-214-6029-4
Kniha
Proceedings I of the 28th Conference STUDENT EEICT 2022 General Papers
Číslo edice
1
Strany od
251
Strany do
254
Strany počet
4
URL
https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2022_sbornik_1_v2.pdf
BibTex
@inproceedings{BUT179425, author="Petra {Nemčeková} and Jana {Schwarzerová}", title="Dynamic metabolomic prediction based on genetic variation for Hordeum vulgare", booktitle="Proceedings I of the 28th Conference STUDENT EEICT 2022 General Papers", year="2022", number="1", pages="251--254", publisher="Brno University of Technology, Faculty of Electrical Engineering and Communication", address="Brno", isbn="978-80-214-6029-4", url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2022_sbornik_1_v2.pdf" }