The large number of markers in genome-wide prediction demands the use of methods with
regularization and model comparison based on some hold-out test prediction error measure …

Genomic prediction is a useful tool for plant and animal breeding programs and is starting to
be used to predict human diseases as well. A shortcoming that slows down the genomic …

Background In genomic prediction, an important measure of accuracy is the correlation
between the predicted and the true breeding values. Direct computation of this quantity for …

Accuracy of genomic prediction is commonly calculated as the Pearson correlation
coefficient between the predicted and observed phenotypes in the inference population by …

Growth of artificial intelligence and machine learning (ML) methodology has been explosive
in recent years. In this class of procedures, computers get knowledge from sets of …

In genomic selection (GS), all the markers across the entire genome are used to conduct
marker-assisted selection such that each quantitative trait locus of complex trait is in linkage …

Background Genomic selection has gained much attention and the main goal is to increase
the predictive accuracy and the genetic gain in livestock using dense marker information …

Phenotyping is the current bottleneck in plant breeding, especially because next-generation
sequencing has decreased genotyping cost more than 100.000 fold in the last 20 years …

Genomic selection (GS) is transforming plant and animal breeding, but its practical
implementation for complex traits and multi-environmental trials remains challenging. To …

Background The goal of genome-wide prediction (GWP) is to predict phenotypes based on
marker genotypes, often obtained through single nucleotide polymorphism (SNP) chips. The …