Machine learning (ML) is perhaps the most useful tool for interpretation of large genomic datasets. However, performance a single machine method in selection (GS) currently unsatisfactory. To improve predictions, we constructed stacking ensemble framework (SELF), integrating three methods, to predict estimated breeding values (GEBVs). The present study evaluated prediction ability SELF by analy...

We investigate two approaches to increase the efficiency of phenotypic prediction from genome-wide markers, which is a key step for genomic selection (GS) in plant and animal breeding. The first approach is feature selection based on Markov blankets, which provide a theoretically-sound framework for identifying non-informative markers. Fitting GS models using only the informative markers result...

One objective of this study was to provide readers with a clear and unified understanding of parametric statistical and kernel methods, used for genomic prediction, and to compare some of these in the context of rice breeding for quantitative traits. Furthermore, another objective was to provide a simple and user-friendly R package, named KRMM, which allows users to perform RKHS regression with...

New proposals for models and applications of prediction processes with data on molecular markers may help reduce the financial costs of and identify superior genotypes in maize breeding programs. Studies evaluating Genomic Best Linear Unbiased Prediction (GBLUP) models including dominance effects have not been performed in the univariate and multivariate context in the data analysis of this cro...

the objective of the present study was to estimate genetic trends for lactation milk yield, persistency of milk yield, somatic cell count and interval between first and second calving in holstein dairy cows of iran. the dataset consisted of 210,625 test day and 25,883 first parity cows with milk yield recorded from july 2002 to september 2007 comprising 97 herds in iran. breeding values of anim...

Genetic selection against boar taint, which is caused by high skatole and androstenone concentrations in fat, is a more acceptable alternative than is the current practice of castration. Genomic predictors offer an opportunity to overcome the limitations of such selection caused by the phenotype being expressed only in males at slaughter, and this study evaluated different approaches to obtain ...

We develop a new genetic prediction method, smooth-threshold multivariate genetic prediction, using single nucleotide polymorphisms (SNPs) data in genome-wide association studies (GWASs). Our method consists of two stages. At the first stage, unlike the usual discontinuous SNP screening as used in the gene score method, our method continuously screens SNPs based on the output from standard univ...

Predicting disease resistance is one of the most prominent applications aquaculture selective breeding. Reductions in genotyping costs have allowed implementation genomic selection an abundance species and their related diseases showing promising results. Machine learning (ML) models can be value for prediction purposes, as suggested by several studies both plants livestock. The current study a...