LGG_2025v16n2

Legume Genomics and Genetics 2025, Vol.16, No.2, 91-99 http://cropscipublisher.com/index.php/lgg 99 Wang K., Abid M., Rasheed A., Crossa J., Hearne S., and Li H., 2022, DNNGP, a deep neural network-based method for genomic prediction using multi-omics data in plants, Molecular Plant, 16(1): 279-293. https://doi.org/10.1016/j.molp.2022.11.004 Watson D., 2021, Interpretable machine learning for genomics, Human Genetics, 141: 1499-1513. https://doi.org/10.1007/s00439-021-02387-9 Yoosefzadeh-Najafabadi M., Earl H., Tulpan D., Sulik J., and Eskandari M., 2021, Application of machine learning algorithms in plant breeding: predicting yield from hyperspectral reflectance in soybean, Frontiers in Plant Science, 11: 624273. https://doi.org/10.3389/fpls.2020.624273 Zhou Y., Liu Y., Wang D., and Liu X., 2021, Comparison of machine-learning models for predicting short-term building heating load using operational parameters, Energy and Buildings, 253: 111505. https://doi.org/10.1016/j.enbuild.2021.111505

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