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1 to 4 of 4 Results
Dataset / Software
May 30, 2020 - CIMMYT Research Data
Montesinos-López, Osval A ; Montesinos-López, José Cricelio; Singh, Pawan; Lozano-Ramirez, Nerida; Barrón-López, Alberto; Montesinos-López, Abelardo; Crossa, Jose, 2020, "Replication Data for: A multivariate Poisson deep learning model for genomic prediction of count data", hdl:11529/10548438, CIMMYT Research Data & Software Repository Network, V1
Genomic selection (GS) is an important method used in plant and animal breeding. The experimental data provided in this study contain counting data. These datasets were used to support research on efficient methodologies for multivariate count data outcomes including a multivaria...
Dataset / Software
May 11, 2020 - CIMMYT Research Data
Ibba, Maria Itria; Crossa, Jose; Montesinos-López, Osval A.; Montesinos-López, Abelardo; Juliana, Philomin; Guzman, Carlos; Dolorean, Emily; Dreisigacker, Susanne ; Poland, Jesse, 2020, "Replication Data for: Genome-based prediction of multiple wheat quality traits in multiple years", hdl:11529/10548423, CIMMYT Research Data & Software Repository Network, V1
The use of genomic prediction could greatly help to increase the efficiency of selecting for wheat quality traits by reducing the cost and time required for this analysis. This study contains data used to evaluate the prediction performances of 13 wheat quality traits under two m...
Dataset / Software
Jul 18, 2019 - CIMMYT Research Data
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
Sep 28, 2018 - CIMMYT Research Data
Montesinos-López, Osval A ; Montesinos-López, Abelardo; Crossa, Jose; Gianola, Daniel ; Hernández-Suárez, Carlos M.; Martín-Vallejo, Javier, 2018, "Supplemental data for multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits", hdl:11529/10548134, CIMMYT Research Data & Software Repository Network, V1
This study provides supplemental data to support an investigation of the power of multi-trait deep learning (MTDL) models in terms of genomic-enabled prediction accuracy.
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