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Author: David González-Diéguez
Molecular pre-breeding in wheat physiology
David González-Diéguez (2023)
Conference object
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT PRE-BREEDING MOLECULAR GENETICS MARKER-ASSISTED SELECTION INTROGRESSION
Genome-based predictions of sub-genome genetic interactions effects in wheat populations
David González-Diéguez (2023)
Conference object
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENOMES WHEAT GENETICS MARKER-ASSISTED SELECTION GENETIC VARIANCE HYBRIDS
Genomic prediction of hybrid crops accounting for non additive genetic effects
David González-Diéguez (2022)
Conference object
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MARKER-ASSISTED SELECTION HYBRIDS MAIZE GENOMES GENETICS GENETIC VARIANCE CROPS
Multimodal deep learning methods enhance genomic prediction of wheat breeding
Carolina Rivera-Amado Francisco Pinto Francisco Javier Pinera-Chavez David González-Diéguez Matthew Paul Reynolds Paulino Pérez-Rodríguez Huihui Li Osval Antonio Montesinos-Lopez Jose Crossa (2023)
Article
Conventional Methods Genomic Prediction Accuracy Deep Learning Novel Methods CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT BREEDING MACHINE LEARNING METHODS MARKER-ASSISTED SELECTION
Replication Data for: Multimodal Deep Learning Methods Enhance Genomic Prediction of Wheat Breeding
Carolina Rivera-Amado Francisco Pinto Francisco Javier Pinera-Chavez David González-Diéguez Paulino Pérez-Rodríguez Huihui Li Osval Antonio Montesinos-Lopez Jose Crossa (2023)
In plant breeding research, several statistical machine learning methods have been developed and studied for assessing the genomic prediction (GP) accuracy of unobserved phenotypes. To increase the GP accuracy of unobserved phenotypes while simultaneously accounting for the complexity of genotype × environment interaction (GE), deep learning (DL) neural networks have been developed.These analyses can potentially include phenomics data obtained through imaging. The two datasets included in this study contain phenomic, phenotypic, and genotypic data for a set of wheat materials. They have been used to compare a novel DL method with conventional GP models.The results of these analyses are reported in the accompanying journal article.
Dataset