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Guillermo Gerard

Showing results (11-20 of 17) with videos related to

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Genes|March 28, 2024
Data Augmentation Enhances Plant-Genomic-Enabled PredictionsOsval A Montesinos-López, Mario Alberto Solis-Camacho, Leonardo Crespo-Herrera, et al.
Frontiers in Plant Science|May 30, 2024
Feature engineering of environmental covariates improves plant genomic-enabled predictionOsval A Montesinos-López, Leonardo Crespo-Herrera, Carolina Saint Pierre, et al.
Frontiers in Plant Science|March 20, 2024
Deep learning methods improve genomic prediction of wheat breedingAbelardo Montesinos-López, Leonardo Crespo-Herrera, Susanna Dreisigacker, et al.
G3 (Bethesda, Md.)|December 11, 2023
A marker weighting approach for enhancing within-family accuracy in genomic predictionOsval A Montesinos-López, Leonardo Crespo-Herrera, Alencar Xavier, et al.
Trends in Plant Science|October 27, 2024
Machine learning algorithms translate big data into predictive breeding accuracyJosé Crossa, Osval A Montesinos-Lopez, Germano Costa-Neto, et al.
Trends in Plant Science|January 31, 2025
Expanding genomic prediction in plant breeding: harnessing big data, machine learning, and advanced softwareJosé Crossa, Johannes W R Martini, Paolo Vitale, et al.
Global Change Biology|August 26, 2024
Wheat genetic resources have avoided disease pandemics, improved food security, and reduced environmental footprints: A review of historical impacts and future opportunitiesJulie King, Susanne Dreisigacker, Matthew Reynolds, et al.
Pageof 2

Showing results (11-20 of 17) with videos related to

Sort By:
Pageof 2
You have reached the last page of results.This site can display upto 17 results.
Genes|March 28, 2024
Data Augmentation Enhances Plant-Genomic-Enabled PredictionsOsval A Montesinos-López, Mario Alberto Solis-Camacho, Leonardo Crespo-Herrera, et al.
Frontiers in Plant Science|May 30, 2024
Feature engineering of environmental covariates improves plant genomic-enabled predictionOsval A Montesinos-López, Leonardo Crespo-Herrera, Carolina Saint Pierre, et al.
Frontiers in Plant Science|March 20, 2024
Deep learning methods improve genomic prediction of wheat breedingAbelardo Montesinos-López, Leonardo Crespo-Herrera, Susanna Dreisigacker, et al.
G3 (Bethesda, Md.)|December 11, 2023
A marker weighting approach for enhancing within-family accuracy in genomic predictionOsval A Montesinos-López, Leonardo Crespo-Herrera, Alencar Xavier, et al.
Trends in Plant Science|October 27, 2024
Machine learning algorithms translate big data into predictive breeding accuracyJosé Crossa, Osval A Montesinos-Lopez, Germano Costa-Neto, et al.
Trends in Plant Science|January 31, 2025
Expanding genomic prediction in plant breeding: harnessing big data, machine learning, and advanced softwareJosé Crossa, Johannes W R Martini, Paolo Vitale, et al.
Global Change Biology|August 26, 2024
Wheat genetic resources have avoided disease pandemics, improved food security, and reduced environmental footprints: A review of historical impacts and future opportunitiesJulie King, Susanne Dreisigacker, Matthew Reynolds, et al.
Pageof 2