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Updated: Jan 22, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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MTMEGPS:使用深度学习进行多特征和多环境的基因组和现象选择的R包

Freddy Mora-Poblete1, Javiera Valenzuela-Herrera2, Matías Balach2

  • 1Institute of Biological Sciences, University of Talca, Talca, Chile.

Frontiers in plant science
|January 21, 2026
PubMed
概括

一个新的R包,MTMEGPS,通过深度学习增强了基因组和现象选择. 它提供了一个用户友好的工作流程,用于在多个特征和环境中预测复杂的特征,提高育种计划的效率.

关键词:
深度学习是一种深度学习.基因组选择 基因组选择超参数优化优化方法分子标记物 分子标记物多种特征和多种环境.频谱信息是一种光谱信息.

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