Contributor Name: CGIAR Research Program on Wheat (WHEAT) Contributor Name: Genetic Resources Program (GRP) Author Name: Crossa, Jose Author Name: Gianola, Daniel Keyword Term: Triticum aestivum Publication Date: 2018
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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. |