CMB_2024v14n4

Computational Molecular Biology 2024, Vol.14, No.4, 145-154 http://bioscipublisher.com/index.php/cmb 154 Varshney R., Roorkiwal M., and Sorrells M., 2017, Genomic selection for crop improvement, Crop Science, 49(1): 1-12. https://doi.org/10.1007/978-3-319-63170-7 Wang T.T., Chen Y.P., and Hayes B., 2016, Accuracy and computational efficiency of genomic selection with high-density SNP and whole-genome sequence data, Cab Reviews: Perspectives in Agriculture Veterinary Science Nutrition and Natural Resources, 2016 (2016): 1-18. https://doi.org/10.1079/PAVSNNR201611034 Wang X., Wang X., Xu Y., Hu Z.L., and Xu C.W., 2018, Genomic selection methods for crop improvement: current status and prospects, The Crop Journal, 6(4): 330-340. https://doi.org/10.1016/J.CJ.2018.03.001 Wang X., Yang Z., and Xu C., 2015, A comparison of genomic selection methods for breeding value prediction, Science Bulletin, 60: 925-935. https://doi.org/10.1007/S11434-015-0791-2 Xu Y.B., Liu X.G., Fu J.J., Wang H., Wang J., Huang C., Prasanna B., Olsen M.S., Wang G.Y., and Zhang A., 2019, Enhancing genetic gain through genomic selection: from livestock to plants, Plant Communications, 1(1): 100005. https://doi.org/10.1016/j.xplc.2019.100005 Yu T.X., Wang L., Zhang W.P., Xing G.F., Han J.W., Li F.Z., and Cao C., 2022, Predicting phenotypes from high-dimensional genomes using gradient boosting decision trees, IEEE Access, 10: 48126-48140. https://doi.org/10.1109/ACCESS.2022.3171341

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