Autor: Saint Pierre, Carolina
- A marker weighting approach for enhancing within-family accuracy in genomic prediction
- Optimizing genomic parental selection for categorical and continuous-categorical multi-trait mixtures
- Deep learning methods improve genomic prediction of wheat breeding
- Machine learning algorithms translate big data into predictive breeding accuracy
- Genotype performance estimation in targeted production environments by using sparse genomic prediction
- Expanding genomic prediction in plant breeding: harnessing big data, machine learning, and advanced software
Autor: Dreisigacker, Susanne
- A marker weighting approach for enhancing within-family accuracy in genomic prediction
- Optimizing genomic parental selection for categorical and continuous-categorical multi-trait mixtures
- Expanding genomic prediction in plant breeding: harnessing big data, machine learning, and advanced software
- Optimizing genomic prediction with transfer learning under a ridge regression framework
- Boosting genomic prediction transferability with sparse testing
- Enhancing wheat genomic prediction by a hybrid kernel approach
Ejemplares similares: A marker weighting approach for enhancing within-family accuracy in genomic prediction
- Optimizing genomic prediction with transfer learning under a ridge regression framework
- Machine learning algorithms translate big data into predictive breeding accuracy
- Improving wheat grain yield genomic prediction accuracy using historical data
- Genotype performance estimation in targeted production environments by using sparse genomic prediction
- Boosting genomic prediction transferability with sparse testing
- Deep learning methods improve genomic prediction of wheat breeding
Ejemplares similares: Optimizing genomic parental selection for categorical and continuous-categorical multi-trait mixtures
- A Bayesian optimization R package for multitrait parental selection
- Bayesian divergence-based approach for genomic multitrait ordinal selection
- Balancing sensitivity and specificity enhances top and bottom ranking in genomic prediction of cultivars
- An assessor-specific Bayesian multi-threshold mixed model for analyzing ordered categorical traits in tree breeding
- Bayesian multitrait kernel methods improve multienvironment genome-based prediction
- Optimizing genomic prediction with transfer learning under a ridge regression framework