Deep learning for genomic selection of aquatic animals

Genomic selection (GS) applied to the breeding of aquatic animals has been of great interest in recent years due to its higher accuracy and faster genetic progress than pedigree-based methods. The genetic analysis of complex traits in GS does not escape the current excitement around artificial intel...

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Veröffentlicht in:	Marine life science & technology Jg. 6; H. 4; S. 631 - 650
Hauptverfasser:	Wang, Yangfan, Ni, Ping, Sturrock, Marc, Zeng, Qifan, Wang, Bo, Bao, Zhenmin, Hu, Jingjie
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Singapore Springer Nature Singapore 01.11.2024
Schlagworte:	Biodiversity Biological Techniques Biomedical and Life Sciences Fish & Wildlife Biology & Management Food Microbiology Freshwater & Marine Ecology Life Sciences Review Deep learning Breeding Genomic selection Future direction Aquaculture Aquatic animals
ISSN:	2662-1746, 2662-1746
Online-Zugang:	Volltext
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