Open AccessApplication of machine learning to explore the genomic prediction accuracy of fall dormancy in autotetraploid alfalfa
Author(s) -
Fan Zhang,
Junmei Kang,
Ruicai Long,
Mingna Li,
Yan Sun,
Fei He,
Xueqian Jiang,
Changfu Yang,
Xijiang Yang,
Jie Kong,
Yiwen Wang,
Zhen Wang,
Zhiwu Zhang,
Qingchuan Yang
Publication year - 2022
Publication title -
horticulture research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.947
H-Index - 31
eISSN - 2662-6810
pISSN - 2052-7276
DOI - 10.1093/hr/uhac225
Subject(s) - biology , support vector machine , quantitative trait locus , genome wide association study , lasso (programming language) , machine learning , artificial intelligence , regression , genomic selection , predictive modelling , computational biology , genetics , statistics , computer science , mathematics , gene , single nucleotide polymorphism , genotype , world wide web
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