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- 4Genomic prediction
- 1Bayesian model
- 1Dairy cattle
- 1Feed efficiency
- 1Genome-wide association study
- 1Genotype imputation
Identification of functional genes for feed efficiency traits via transcriptome analyses to enhance the genomic prediction accuracy in beef cattleDownload
Residual feed intake (RFI), a measure of feed efficiency, and its component traits including average daily gain (ADG), dry matter intake (DMI) and metabolic weight (MWT) are traits of great economic importance to the beef industry. The genetic improvement of these traits can improve the...
Improving Accuracy of Genomic Prediction for Economically Important Traits in Canadian Holstein Dairy CattleDownload
Milk is a valuable source of energy, high quality protein, and several key minerals and vitamins for humans. Selection for milk production in dairy cattle was first based on phenotype and pedigree information and the knowledge of genetic parameters for the trait of interest. However, substantial...
Background Genomic prediction in multiple populations can be viewed as a multi-task learning problem where tasks are to derive prediction equations for each population and multi-task learning property can be improved by sharing information across populations. The goal of this study was to...
In this dissertation, I focus on the study of genotype imputation in population data. Genotype imputation is a process of inferring missing values for genotype data and has been extended to predicting “untyped” genotypes for samples in low-density chips with a reference population assayed using...