Genomic prediction using machine learning: a comparison of the performance of regularized regression, ensemble, instance-based and deep learning methods on synthetic and empirical data

Genomic prediction using machine learning: a comparison of the performance of regularized regression, ensemble, instance-based and deep learning methods on synthetic and empirical data

Abstract Background The accurate prediction of genomic breeding values is central to genomic selection in both plant and animal breeding studies. Genomic prediction involves the use of thousands of molecular markers spanning the entire genome and therefore requires methods able to efficiently handle...

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Bibliographic Details
Main Authors: Vanda M. Lourenço, Joseph O. Ogutu, Rui A.P. Rodrigues, Alexandra Posekany, Hans-Peter Piepho
Format: Article
Language:English
Published: BMC 2024-02-01
Series:BMC Genomics
Subjects:
Genomic prediction
Genomic selection
Breeding value
Predictive accuracy
Predictive ability
High-dimensional data
Online Access:https://doi.org/10.1186/s12864-023-09933-x

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