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| Genomic Selection for Adjacent Genetic Markers of Yorkshire Pigs Using Regularized Regression Approaches |
| Minsu Park, Tae-Hun Kim, Eun-Seok Cho, Heebal Kim, Hee-Seok Oh |
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Anim Biosci. 2014;27(12):1678-1683. Published online October 16, 2014 DOI: https://doi.org/10.5713/ajas.2014.14236 |
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Genomic Selection for Adjacent Genetic Markers of Yorkshire Pigs Using Regularized Regression Approaches Asian-Australasian Journal of Animal Sciences. 2014;27(12):1678-1683  Genomic selection using regularized linear regression models: ridge regression, lasso, elastic net and their extensions BMC Proceedings. 2012;6(S2): Integrated Framework for Selection of Additive and Nonadditive Genetic Markers for Genomic Selection Journal of Computational Biology. 2020;27(6):845-855 Genomic breeding value estimation using nonparametric additive regression models Genetics Selection Evolution. 2009;41(1): Genomic selection using principal component regression Heredity. 2018;121(1):12-23 Genomic selection using low density marker panels with application to a sire line in pigs Genetics Selection Evolution. 2013;45(1): Class prediction and gene selection for DNA microarrays using regularized sliced inverse regression Computational Statistics & Data Analysis. 2007;52(1):438-451 Improving stability and understandability of genotype-phenotype mapping in Saccharomyces using regularized variable selection in L-PLS regression BMC Bioinformatics. 2012;13(1): Prediction of genetic merit for growth rate in pigs using animal models with indirect genetic effects and genomic information Genetics Selection Evolution. 2020;52(1): Feature selection under regularized orthogonal least square regression with optimal scaling Neurocomputing. 2018;273:547-553 |
