Bayesian neural networks for genomic prediction: uncertainty quantification and SNP interpretation with SHAP and GWAS.

Abstract excerpt

KEY MESSAGE: This study presents a Bayesian neural networks framework with LASSO regularization and the GSMeSP interpretability tool, enabling accurate, uncertainty-aware, and biologically interpretable genomic prediction. Deep learning offers significant potential for genomic prediction by modeling complex, nonlinear genotype-phenotype relationships. However, its application in plant breeding has been...

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• Bayes Theorem
• Genome, Plant
• Genomics
• Gossypium
• Models, Genetic