Genomic prediction powered by multi-omics data
Genomic selection (GS) has transformed plant breeding by enabling early and accurate prediction of complex traits. However, its predictive performance is often constrained by the limited information captured through genomic markers alone, especially for traits influenced by intricate biological path...
| Autores principales: | , , , , , , , , |
|---|---|
| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Frontiers Media
2025
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/179104 |
Ejemplares similares: Genomic prediction powered by multi-omics data
- Boosting genomic prediction transferability with sparse testing
- Balancing sensitivity and specificity enhances top and bottom ranking in genomic prediction of cultivars
- A graph model for genomic prediction in the context of a linear mixed model framework
- Optimizing genomic prediction with transfer learning under a ridge regression framework
- Using an incomplete block design to allocate lines to environments improves sparse genome-based prediction in plant breeding
- Refining penalized ridge regression: a novel method for optimizing the regularization parameter in genomic prediction