Shunzhe Wang

From linear models to deep learning: statistical advances in genomic selection for animal breeding

A comprehensive overview of GS methodologies is provided, first covering the statistical foundations of linear mixed and Bayesian models, and then modern ML and DL approaches, to provide practical guidance for optimizing genomic evaluation strategies in the era of big data breeding.