ArticleFrontiers in genetics2021
TrainSel: An R Package for Selection of Training Populations.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Unveiling the interactions between design optimization, modeling strategies, and spatial analysis in genomic selection.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- MateR: a novel genomic mating framework.Genetics · 2026Article
- Optimizing training sets for genomic selection to identify superior genotypes across multiple environments.G3 (Bethesda, Md.) · 2026Article
- Exploring the Frontiers of Computational NMR: Methods, Applications, and Challenges.Chemical reviews · 2025Review
- Sparse testing designs for optimizing resource allocation in multi-environment cassava breeding trials.The plant genome · 2025Article
- Optimizing core collections for genetic studies: a worldwide flax germplasm case study.Frontiers in plant science · 2025Article
- Evaluation of genomic mating approach based on genetic algorithms for long-term selection in Huaxi cattle.BMC genomics · 2024Article
- Genomic selection optimization in blueberry: Data-driven methods for marker and training population design.The plant genome · 2024Article
- Maximizing efficiency in sunflower breeding through historical data optimization.Plant methods · 2024Article
- A comparison of design algorithms for choosing the training population in genomic models.Frontiers in genetics · 2024Article
- Training set optimization is a feasible alternative for perennial orphan crop domestication and germplasm management: anFrontiers in plant science · 2024Article
- Stochastic simulation to optimize rice breeding at IRRI.Frontiers in plant science · 2024Article
- Optimization of Multi-Generation Multi-location Genomic Prediction Models for Recurrent Genomic Selection in an Upland Rice Population.Rice (New York, N.Y.) · 2023Article
- Genetic gain and inbreeding from simulation of different genomic mating schemes for pig improvement.Journal of animal science and biotechnology · 2023Article
- Genetic Basis of Resistance toPlants (Basel, Switzerland) · 2023Article
- Oracle selection provides insight into how far off practice is from Utopia in plant breeding.Frontiers in plant science · 2023Article
- Assessment of genomic prediction reliability and optimization of experimental designs in multi-environment trials.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Article
- Building a Calibration Set for Genomic Prediction, Characteristics to Be Considered, and Optimization Approaches.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Evaluation of Genomic Prediction for Fusarium Head Blight Resistance with a Multi-Parental Population.Biology · 2021Article
- Training Set Optimization for Sparse Phenotyping in Genomic Selection: A Conceptual Overview.Frontiers in plant science · 2021Article
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Authors and funding
3 authors.
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Abstract
A major barrier to the wider use of supervised learning in emerging applications, such as genomic selection, is the lack of sufficient and representative labeled data to train prediction models. The amount and quality of labeled training data in many applications is usually limited and therefore careful selection of the training examples to be labeled can be useful for improving the accuracies in predictive learning tasks. In this paper, we present an R package, TrainSel, which provides flexible, efficient, and easy-to-use tools that can be used for the selection of training populations (STP). We illustrate its use, performance, and potentials in four different supervised learning applications within and outside of the plant breeding area.
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