Haplotype-based autoencoders can reduce the dataset dimension and estimate haplotype block effects in different crop species

Abstract Background In plant breeding, many studies currently investigate the application of machine learning (ML) to genomic prediction, hoping for an improvement in prediction accuracy compared to standard models like Genomic Best Linear Unbiased Prediction (GBLUP). However, ML algorithms require...

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Detalhes bibliográficos

Principais autores:	Philipp Georg Heilmann, Emanuel Grosch, Matthias Frisch, Matthias Herrmann, Steffen Beuch, Vivek Kurra, Martin Mascher, Raz Avni, Klaus Oldach, Ina Röhrs, Anja Hanemann, Raja Ram Mehta, Carsten Reinbrecht, Albrecht Serfling, Andreas Stahl, Marco Stucke, Amine Abbadi, Tobias Kox, Carola Zenke-Philippi
Formato:	Artigo
Idioma:	Inglês
Publicado em:	BMC 2025-12-01
coleção:	BMC Bioinformatics
Assuntos:	Plant breeding Machine learning Genomic prediction Neural networks Autoencoders Dimensionality reduction
Acesso em linha:	https://doi.org/10.1186/s12859-025-06323-w
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