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1 to 10 of 24 Results
Dataset / Software
Jul 12, 2019
Howard, Reka; Gianola, Daniel; Montesinos-López, Osval; Juliana, Philomin; Singh, Ravi; Poland, Jesse; Shrestha, Sandesh; Perez-Rodriguez, Paulino; Crossa, Jose; Jarquin, Diego, 2019, "Replication Data for: Joint use of genome, pedigree and their interaction with environment for predicting the performance of wheat lines in new environments", hdl:11529/10548169, CIMMYT Research Data & Software Repository Network, V3
In this study, we evaluated genome-based prediction using 35,403 wheat lines from the Global Wheat Breeding Program of the International Maize and Wheat Improvement Center (CIMMYT). We implemented eight statistical models that included genome-wide molecular marker and pedigree in...
Dataset / Software
Apr 26, 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, V3
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
Oct 30, 2018
Poland, Jesse; Dreisigacker, Susanne; Shrestha, Sandesh; Wu, Shuangye; Singh, Ravi; Mondal, Suchismita; Juliana, Philomin; Crossa, Jose; Rutkoski, Jessica, 2016, "Genotypic data from CIMMYT bread wheat breeding lines used in the Feed the Future Innovation Lab for Applied Wheat Genomics", hdl:11529/10695, CIMMYT Research Data & Software Repository Network, V2
Genetic profiling of wheat breeding lines from the CIMMYT bread wheat breeding program was carried out over several years. Unimputed genotypic data in the VCF format (CIMMYT-2013-2018.hmp.vcf) for 91,680 markers are available upon request. We could not upload and publish the unim...
Dataset / Software
Oct 26, 2018
Montesinos-López, Osval A ; Montesinos-López, Abelardo; Crossa, Jose; Cuevas, Jaime; Montesinos-López, José Cricelio; Gutiérrez, Zitlalli Salas; Lillemo, Morten; Juliana, Philomin; Singh, Ravi, 2018, "A Bayesian genomic multi-output regressor stacking model for predicting multi-trait multi-environment plant breeding data", hdl:11529/10548141, CIMMYT Research Data & Software Repository Network, V1
A new statistical model is presented for genomic prediction on maize and wheat data comprising multi-trait, multi-environment data.
Dataset / Software
Oct 22, 2018
Montesinos-López, Osval A ; Martín-Vallejo, Javier; Crossa, Jose; Gianola, Daniel ; Hernández-Suárez, Carlos M.; Montesinos-López, Abelardo; Juliana, Philomin; Singh, Ravi, 2018, "New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes", hdl:11529/10548140, CIMMYT Research Data & Software Repository Network, V1
The seven data sets are wheat data from CIMMYT Global Wheat Breeding program. They comprise different traits, like days to heading, days to maturity, grain yield, grain color, different type of leaf and stripe rust in wheat. Also the trials were run in different environments.
Dataset / Software
Oct 8, 2018
Cerón-Rojas, J.Jesús; Toledo, Fernando; Crossa, Jose, 2018, "Supplemental Materials for The Relative Efficiency of Three Constrained Multistage Linear Phenotypic Selection Indices", hdl:11529/10548136, CIMMYT Research Data & Software Repository Network, V1
This dataset provides supplemental information related to an investigation of constrained multistage linear phenotypic selection indices.
Dataset / Software
Sep 28, 2018
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.
Dataset / Software
Jun 13, 2018
Montesinos-López, Abelardo; Montesinos-López, Osval A; Gianola, Daniel; Crossa, Jose, 2018, "Deep learning genomic-enabled prediction of plant traits", hdl:11529/10548082, CIMMYT Research Data & Software Repository Network, V1
Machine learning (ML) is a field of computer science that uses statistical techniques to give computer systems the ability to "learn" (i.e., progressively improve performance on a specific task) from data, without being explicitly programmed to do this. ML is closely related to (...
Dataset / Software
Oct 10, 2017
Montesinos-Lopez, Osval A.; Montesinos-Lopez, Abelardo; Crossa, Jose; Montesinos-Lopez, Jose C.; Mota-Sanchez, David; Estrada-Gonzalez, Fermin; Gilberg, Jussi; Singh, Ravi; Mondal, Suchismita; Juliana, Philomin, 2017, "Prediction of multiple-trait and multiple-environment genomic data using recommender systems", hdl:11529/11099, CIMMYT Research Data & Software Repository Network, V2
In genomic-enabled prediction, the task of improving the accuracy of the prediction of lines in environments is difficult because the available information is generally sparse and usually has low correlations between traits. In current genomic selection, while researchers have a...
Dataset / Software
May 12, 2017
Torres Flores, Jose Luis; Garcia, Beatriz Mendoza; Boddupalli, Maruthi Prasanna; Alvarado, Gregorio; San Vicente, Felix M.; Crossa, Jose, 2017, "Grain yield and stability of white early hybrids in the highland valleys of Mexico", hdl:11529/10934, CIMMYT Research Data & Software Repository Network, V2
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