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Genomic selection using regularized linear regression models: ridge regression, lasso, elastic net and their extensions
BACKGROUND: Genomic selection (GS) is emerging as an efficient and cost-effective method for estimating breeding values using molecular markers distributed over the entire genome. In essence, it involves estimating the simultaneous effects of all genes or chromosomal segments and combining the estim...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2012
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3363152/ https://www.ncbi.nlm.nih.gov/pubmed/22640436 http://dx.doi.org/10.1186/1753-6561-6-S2-S10 |