Author

A. Nascimento

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Open access 2026

Integrating autoencoder deep neural networks with principal component-based methods for subpopulation identification

Abstract This study evaluated statistical dimensionality reduction techniques, Principal Component Analysis (PCA), Sparse PCA (SPCA), Independent PCA (IPCA), deep learning based on autoencoders (AE), and their hybrid combinations, for subpopulation identification in genomic data. High-dimensional single nucleotide poly...

C. Azevedo, J. A. da Costa, A. Nascimento et al. · Crop Breeding and Applied Bi... · 0 citations

Open access Sep 2026

Non-linear kernel methods for genomic prediction of soybean yield and quality in multi-environment trials

Nonlinear kernels improve the accuracy of genomic prediction while preserving the inferential framework of quantitative genetics. Improving the predictive accuracy of genomic prediction (GP) for complex genetic architectures involving non-additive effects and genotype-by-environment interactions (GEI) requires alternat...

Wanessa Alves Lima Paiva, W. G. da Costa, Leandro Pacheco Machado et al. · Theoretical and Applied Gene... · 0 citations