Cargando…
Combining Genomic and Genealogical Information in a Reproducing Kernel Hilbert Spaces Regression Model for Genome-Enabled Predictions in Dairy Cattle
Genome-enhanced genotypic evaluations are becoming popular in several livestock species. For this purpose, the combination of the pedigree-based relationship matrix with a genomic similarities matrix between individuals is a common approach. However, the weight placed on each matrix has been so far...
Autores principales: | Rodríguez-Ramilo, Silvia Teresa, García-Cortés, Luis Alberto, González-Recio, Óscar |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3966896/ https://www.ncbi.nlm.nih.gov/pubmed/24671175 http://dx.doi.org/10.1371/journal.pone.0093424 |
Ejemplares similares
-
Reproducing kernel hilbert spaces in probability and statistics
por: Berlinet, Alain, et al.
Publicado: (2004) -
A primer on reproducing kernel Hilbert spaces
por: Manton, Jonathan H, et al.
Publicado: (2015) -
High-Order Sequential Simulation via Statistical Learning in Reproducing Kernel Hilbert Space
por: Yao, Lingqing, et al.
Publicado: (2019) -
Combining Dissimilarities in a Hyper Reproducing Kernel Hilbert Space for Complex Human Cancer Prediction
por: Martín-Merino, Manuel, et al.
Publicado: (2009) -
A guide for kernel generalized regression methods for genomic-enabled prediction
por: Montesinos-López, Abelardo, et al.
Publicado: (2021)