Improved genomic prediction using machine learning with Variational Bayesian sparsity

Improved genomic prediction using machine learning with Variational Bayesian sparsity

Abstract Background Genomic prediction has become a powerful modelling tool for assessing line performance in plant and livestock breeding programmes. Among the genomic prediction modelling approaches, linear based models have proven to provide accurate predictions even when the number of genetic ma...

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Bibliographic Details
Main Authors: Qingsen Yan, Mario Fruzangohar, Julian Taylor, Dong Gong, James Walter, Adam Norman, Javen Qinfeng Shi, Tristan Coram
Format: Article
Language:English
Published: BMC 2023-09-01
Series:Plant Methods
Subjects:
Machine learning
Genomic prediction
Linear mixed models
Bayesian
Variational inference
Feature selection
Online Access:https://doi.org/10.1186/s13007-023-01073-3

Internet

https://doi.org/10.1186/s13007-023-01073-3

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