Applications of Machine Learning in Breeding for Stress Tolerance in Maize
- 18 October 2011
- book chapter
- Published by Springer Nature
Abstract
No abstract availableThis publication has 74 references indexed in Scilit:
- Finding quantitative trait loci genes with collaborative targeted maximum likelihood learningStatistics & Probability Letters, 2011
- Genome-wide selection by mixed model ridge regression and extensions based on geostatistical modelsBMC Proceedings, 2010
- Genomic selection in plant breeding: from theory to practiceBriefings in Functional Genomics, 2010
- Systemic properties of metabolic networks lead to an epistasis-based model for heterosisTheoretical and Applied Genetics, 2009
- Advances in Maize Genomics and Their Value for Enhancing Genetic Gains from BreedingInternational Journal of Plant Genomics, 2009
- Molecular Plant Breeding as the Foundation for 21st Century Crop ImprovementPlant Physiology, 2008
- Quantitative Trait Loci and Crop Performance under Abiotic Stress: Where Do We Stand?: Table I.Plant Physiology, 2008
- Precision-mapping and statistical validation of quantitative trait loci by machine learningBMC Genomic Data, 2008
- Detecting the number of clusters of individuals using the software structure: a simulation studyMolecular Ecology, 2005
- Diversity creation methods: a survey and categorisationInformation Fusion, 2004