A review of deep learning applications for genomic selection

A review of deep learning applications for genomic selection

Abstract Background Several conventional genomic Bayesian (or no Bayesian) prediction methods have been proposed including the standard additive genetic effect model for which the variance components are estimated with mixed model equations. In recent years, deep learning (DL) methods have been cons...

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Bibliographic Details
Main Authors: Osval Antonio Montesinos-López, Abelardo Montesinos-López, Paulino Pérez-Rodríguez, José Alberto Barrón-López, Johannes W. R. Martini, Silvia Berenice Fajardo-Flores, Laura S. Gaytan-Lugo, Pedro C. Santana-Mancilla, José Crossa
Format: Article
Language:English
Published: BMC 2021-01-01
Series:BMC Genomics
Subjects:
Genomic selection
Deep learning
Plant breeding
Genomic trends
Online Access:https://doi.org/10.1186/s12864-020-07319-x

Internet

https://doi.org/10.1186/s12864-020-07319-x

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