Genome-Wide Prediction of Complex Traits in Two Outcrossing Plant Species Through Deep Learning and Bayesian Regularized Neural Network

Genome-Wide Prediction of Complex Traits in Two Outcrossing Plant Species Through Deep Learning and Bayesian Regularized Neural Network

Genomic selection models were investigated to predict several complex traits in breeding populations of Zea mays L. and Eucalyptus globulus Labill. For this, the following methods of Machine Learning (ML) were implemented: (i) Deep Learning (DL) and (ii) Bayesian Regularized Neural Network (BRNN) bo...

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Bibliographic Details
Main Authors: Carlos Maldonado, Freddy Mora-Poblete, Rodrigo Iván Contreras-Soto, Sunny Ahmar, Jen-Tsung Chen, Antônio Teixeira do Amaral Júnior, Carlos Alberto Scapim
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-11-01
Series:Frontiers in Plant Science
Subjects:
deep learning
Bayesian regularized neural network
genomic prediction
machine learning
single-nucleotide polymorphisms
tropical maize
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2020.593897/full

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https://www.frontiersin.org/articles/10.3389/fpls.2020.593897/full

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