… the prediction accuracy of different genomic prediction models for crop species differing in LD
and marker density, for traits … -to-testing population affected prediction accuracy. To build a …

… exploit the correlation between traits, which many times helps improve prediction accuracy.
For … of multi-trait deep learning (MTDL) models in terms of prediction accuracy. The prediction …

… We expect that multi-trait methods for genomic prediction carry great promise to accelerate
both plant and animal breeding. However there is a need to design better methods to …

… trait whose genetic architecture could never be known in practice. Computational efficiency
is an important requirement for the application of genomic selection and genomic prediction (…

… factors affecting prediction ability. Our results showed the relevance of using multi-trait GS
models to achieve increased predictions. Genetic architecture of the target trait and genetic …

… in genomic prediction analyses. Four weighting factors for building a trait-specific genomic
… The objective of this study was to compare results from genomic prediction analyses using …

… Here, we apply a genomic prediction approach to estimate breeding values of … Genomic
and pedigree-based approaches gave largely consistent results. Thus, using genomic prediction …

… Genomic prediction is a method of using markers to predict the genetic value of complex traits
… When genomic prediction is used for selection, it is called genomic selection (GS). GS is a …

… of genomic prediction for traits with relatively low heritability and poor prediction accuracy, …
multi-trait models using a relationship matrix based only on prioritized markers. Our primary …

… genome association and prediction for various traits of interest in grapevine breeding, likely
to display different genetic architectures… , how accurate genomic prediction might be, and …