Application of a Poisson deep neural network model for the prediction of count data in genome‐based prediction-Reference-Cited by-同舟云学术

Application of a Poisson deep neural network model for the prediction of count data in genome‐based prediction

Published:2021-07-29 Issue:3 Volume:14 Page:
ISSN:1940-3372
Container-title:The Plant Genome
language:en
Short-container-title:Plant Genome

Author:

Montesinos‐Lopez Osval A.¹,Montesinos‐Lopez Jose C.²,Salazar Eduardo¹,Barron Jose Alberto³,Montesinos‐Lopez Abelardo⁴,Buenrostro‐Mariscal Raymundo¹,Crossa Jose⁵⁶^ORCID

Affiliation:

1. Facultad de Telemática Univ. de Colima Colima Colima 28040 México

2. Dep. de Estadística Centro de Investigación en Matemáticas Guanajuato Guanajuato 36023 México

3. Dep. of Animal Production (DPA) Universidad Nacional Agraria La Molina Av. La Molina, s/n La Molina 15024 Lima Perú

4. Dep. de Matemáticas Centro Universitario de Ciencias Exactas e Ingenierías, Univ. de Guadalajara Guadalajara Jalisco 44430 México

5. Biometrics and Statistics Unit International Maize and Wheat Improvement Center (CIMMYT) Carretera km 45, Mexico‐Veracruz Texcoco Edo. de México CP 52640 México

6. Colegio de Post‐Graduados CP 56230, Montecillos, Edo. de México Texcoco México

Publisher

Wiley

Subject

Plant Science,Agronomy and Crop Science,Genetics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/tpg2.20118

Reference38 articles.

1. Genomic Selection for Processing and End‐Use Quality Traits in the CIMMYT Spring Bread Wheat Breeding Program

2. Can Deep Learning Improve Genomic Prediction of Complex Human Traits?

3. Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars

4. Genomic Selection in Plant Breeding: Methods, Models, and Perspectives

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