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机器学习全基因组选择研究进展

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机器学习方法是全基因组选择研究的重要分支,深度学习是近年来机器学习领域新的研究热点.本文介绍了机器学习以及深度学习全基因组选择研究的原理和应用发展,分别从模型框架、模型参数、特征选择等方面对深度学习全基因组育种值估计研究进展进行了阐述,探讨了深度学习全基因组选择研究中面临的一些的问题,并对未来进行了展望.
Research Progress in Machine Learning Genomic Selection
Machine learning method is an important branch of genomic selection,and deep learn-ing has become a new research hotspot in the field of machine learning in recent years.The prin-ciples and application development of machine learning and deep learning genomic selection were introduced in this paper,and the research progress of deep learning genomic breeding value esti-mation from the aspects of model framework,model parameters,feature selection were elabora-ted.Some problems in deep learning genomic selection research were explored and prospects in the future were discussed.

genomic selectionresearch progressmachine learningdeep learningprinciples and applications

李竟、张元旭、王泽昭、陈燕、徐凌洋、张路培、高雪、高会江、李俊雅、朱波、郭鹏

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天津农学院计算机与信息工程学院,天津 300384

中国农业科学院北京畜牧兽医研究所,北京 100193

全基因组选择 研究进展 机器学习 深度学习 原理与应用

国家自然科学基金

32272843

2024

畜牧兽医学报
中国畜牧兽医学会

畜牧兽医学报

CSTPCD北大核心
影响因子:0.729
ISSN:0366-6964
年,卷(期):2024.55(6)
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