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Genetics|October 29, 2024
MegaLMM improves genomic predictions in new environments using environmental covariatesHaixiao Hu, Renaud Rincent, Daniel E Runcie
International Journal of Molecular Sciences|December 11, 2022
Multi-Trait Genomic Prediction Improves Accuracy of Selection among Doubled Haploid Lines in MaizeHaixiao Hu, Yujie Meng, Wenxin Liu, et al.
Frontiers in Plant Science|July 9, 2020
Combining Crop Growth Modeling With Trait-Assisted Prediction Improved the Prediction of Genotype by Environment InteractionsPauline Robert, Jacques Le Gouis, , et al.
Methods in Molecular Biology (Clifton, N.J.)|April 22, 2022
Phenomic Selection: A New and Efficient Alternative to Genomic SelectionPauline Robert, Charlotte Brault, Renaud Rincent, et al.
Plos Genetics|February 9, 2019
Fast and flexible linear mixed models for genome-wide geneticsDaniel E Runcie, Lorin Crawford
Genetics|May 3, 2013
Dissecting high-dimensional phenotypes with bayesian sparse factor analysis of genetic covariance matricesDaniel E Runcie, Sayan Mukherjee
The Plant Genome|March 30, 2026
Multi-environment evaluation and genomic prediction of agronomic traits in the southern US rice genepoolMary-Francis LaPorte, Haixiao Hu, Walter Solomon, et al.
TAG. Theoretical and Applied Genetics. Theoretische Und Angewandte Genetik|October 19, 2023
Plasticity QTLs specifically contribute to the genotype × water availability interaction in maizeYacine Djabali, Renaud Rincent, Marie-Laure Martin, et al.
Plos One|March 28, 2020
Wheat individual grain-size variance originates from crop development and from specific genetic determinismAurore Beral, Renaud Rincent, Jacques Le Gouis, et al.
The Plant Genome|January 8, 2025
Improvement in genomic prediction of maize with prior gene ontology information depends on traits and environmental conditionsBaber Ali, Tristan Mary-Huard, Alain Charcosset, et al.
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