ArticleMammalian genome : official journal of the International Mammalian Genome Society2025
The effect of different approaches to determining the regularization parameter of bayesian LASSO on the accuracy of genomic prediction.
Article in Mammalian genome : official journal of the International Mammalian Genome Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Integrating GWAS-guided markers preselection with genomic selection enhances prediction of pulpwood-related traits in slash pine (Pinus elliottii Englem.).BMC plant biology · 2026Article
- Feed-forward neural networks for genomic selection: insights into varying levels of dominance heritability.BMC genomics · 2026Article
- Different approaches for estimating the shrinkage factor in ridge regression BLUP for genomic selection.Scientific reports · 2025Article
- Predicting Radiation Esophagitis in Patients Undergoing Synchronous Boost Radiotherapy Post-Breast-Conserving Surgery.Dose-response : a publication of International Hormesis SocietyArticle
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Authors and funding
3 authors.
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Abstract
Using dense genomic markers opens up new opportunities and challenges for breeding programs. The need to penalize marker-specific regression coefficients becomes particularly important when dense markers are available. Therefore, fitting the marker effects to observations using a regularization technique, such as Bayesian LASSO (BL) regression, is of great interesting. When the Laplace prior distribution is applied to the regression coefficients, BL can be interpreted as a regularization of the
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