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1 to 10 of 11 Results
Dataset / Software
Aug 15, 2019
Crossa, Jose; Martini, Johannes; Gianola, Daniel; Pérez-Rodríguez, Paulino; Burgueño, Juan; Singh, Ravi; Juliana, Philomin; Montesinos-López, Osval; Cuevas, Jaime, 2019, "Deep kernel and deep learning for genomic-based prediction", hdl:11529/10548273, CIMMYT Research Data & Software Repository Network, V1
Deep learning (DL) is a promising method in the context of genomic prediction for selecting individuals early in time without measuring their phenotypes. iI this paper we compare the performance in terms of genome-based prediction of the DL method, deep kernel (arc-cosine kernel,...
Dataset / Software
Jul 18, 2019
Cuevas, Jaime; Montesinos-López, Osval A; Juliana, Philomin; Pérez-Rodríguez, Paulino; Burgueño, Juan; Guzman, Carlos; Montesinos-López, Abelardo; Crossa, Jose, 2019, "Deep kernel of genomic and near infrared predictions in multi-environment breeding trials", hdl:11529/10548180, CIMMYT Research Data & Software Repository Network, V4
In genomic prediction deep learning artificial neural network are part of machine learning methods that incorporate parametric, non-parametric and semi-parametric statistical models. Kernel methods are seeing more flexible, and easier to interpret than neural networks. Kernel met...
Dataset / Software
Nov 9, 2018
Granato, Italo; Cuevas, Jaime; Luna, Francisco; Crossa, José; Burgueño, Juan; Fritsche-Neto, Roberto, 2018, "BGGE: A new package for genomic prediction incorporating genotype by environments models", hdl:11529/10548107, CIMMYT Research Data & Software Repository Network, V5
One of the major issues in plant breeding is the occurrence of genotype by environment (GE) interaction. Several models have been created to understand this phenomenon and explore it by selecting the most stable genotypes. In the genomic era, several models were employed to simul...
Dataset / Software
Feb 16, 2017
Bandeira e Sousa, Massaine; Cuevas, Jaime; Oliveira Couto, Evellyn Giselly de; Pérez-Rodríguez, Paulino; Jarquín, Diego; Fritsche-Neto, Roberto; Burgueño, Juan; Crossa, Jose, 2017, "Genomic-enabled prediction in maize using kernel models with genotype × environment interaction", hdl:11529/10887, CIMMYT Research Data & Software Repository Network, V1
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Dataset / Software
Sep 12, 2016
Cuevas, Jaime; Crossa, José; Montesinos-López, Osval Antonio; Burgueño, Juan; Pérez-Rodríguez, Paulino; Campos, Gustavo de los, 2016, "Bayesian genomic prediction with genotype × environment interaction kernel models", hdl:11529/10710, CIMMYT Research Data & Software Repository Network, V1
The phenomenon of genotype × environment (G×E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G×E have been recently developed and used in genomic selection of plant breeding...
Dataset / Software
Jul 20, 2016
Montesinos-López, Osval Antonio; Montesinos-López, Abelardo; Crossa, José; Campos, Gustavo de los; Alvarado, Gregorio; Mondal, Suchismita; Rutkoski, Jessica; Pérez-González, Lorena; Burgueño, Juan, 2016, "Prediction models for canopy hyperspectral reflectance in wheat breeding data", hdl:11529/10693, CIMMYT Research Data & Software Repository Network, V1
Vegetation indices (VI) generated by using some bands from hyperspectral cameras are used as predictors of primary traits. This study proposes models that use all available bands as predictors of primary traits. The proposed models were ordinal least square (OLS), Bayes B, princi...
Dataset / Software
Jul 11, 2016
Crossa, Jose; Pérez-Rodriguez, Paulino; de los Campos, Gustavo; Burgueño, Juan; Roorkiwal, Manish; Montesinos-Lopez, Osval; Beyene, Yoseph; Pandey, Manish K.; Singh, Vikas K.; Jarquín, Diego; Zhang, Xuecai; Rutkoski, Jessica; Singh, Ravi; Varshney, Rajeev K., 2016, "Genomic Selection in Plant Breeding: Advances and Perspectives", hdl:11529/10687, CIMMYT Research Data & Software Repository Network, V1
Dataset / Software
Feb 15, 2016
Montesinos-López, Abelardo; Montesinos-López, Osval A.; Crossa, Jose; Burgueño, Juan; Eskridge, Kent M.; Falconi, Esteban; Singh, Pawan; He, Xinyao, 2015, "Genomic Bayesian Prediction Model for Count Data with Genotype × Environment Interaction", hdl:11529/10575, CIMMYT Research Data & Software Repository Network, V2
Genomic tools allow the study of the whole genome and are facilitating the study of genotype-environment combinations and their relationship with the phenotype. However, most genomic prediction models developed so far are appropriate for Gaussian phenotypes. For this reason, appr...
Dataset / Software
Jan 25, 2016
Jarquín, Diego; Pérez-Elizalde, Sergio; Burgueño, Juan; Crossa, José, 2015, "A Hierarchical Bayesian Estimation Model for Multi-Environment Plant Breeding Trials in Successive Years", hdl:11529/10463, CIMMYT Research Data & Software Repository Network, V2
In agriculture and plant breeding, multi-environment trials over multiple years are conducted to evaluate and predict genotypic performance under different environmental conditions, and to analyze, study, and interpret genotype × environment interaction (G×E). In this study, we p...
Dataset / Software
Sep 21, 2015
Montesinos-López, Osval Antonio; Montesinos-López, Abelardo; Crossa, José; Burgueño, Juan; Eskridge, Kent, 2015, "Genomic-Enabled Prediction of Ordinal Data with Bayesian Logistic Ordinal Regression", hdl:11529/10254, CIMMYT Research Data & Software Repository Network, V5
Most genomic-enabled prediction models developed so far assume that the response variable is continuous and normally distributed. The exception is the probit model developed for ordered categorical phenotypes. In statistical applications, due to the easy implementation of the Bay...
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