Ben J. Hayes mainly investigates Genetics, Quantitative trait locus, Single-nucleotide polymorphism, Selection and SNP. His Quantitative trait locus research integrates issues from Genome-wide association study, Best linear unbiased prediction, Genetic association, Heritability and Genetic variation. The study incorporates disciplines such as Statistics, Genetic gain and Animal science in addition to Best linear unbiased prediction.
His research on Single-nucleotide polymorphism also deals with topics like
Genetics, Single-nucleotide polymorphism, Quantitative trait locus, Selection and Biotechnology are his primary areas of study. His works in SNP, Genome-wide association study, Genetic variation, Linkage disequilibrium and Genome are all subjects of inquiry into Genetics. His studies in Single-nucleotide polymorphism integrate themes in fields like Dairy cattle and Allele, Haplotype.
His Quantitative trait locus research is multidisciplinary, relying on both Best linear unbiased prediction, Explained variation, Family-based QTL mapping and Heritability. His Selection research focuses on Genetic gain and how it relates to Breeding program. His research integrates issues of Genomic selection, Agriculture, Plant breeding and Animal science, Animal breeding in his study of Biotechnology.
His scientific interests lie mostly in Genetics, Selection, Quantitative trait locus, Genetic variation and Genetic gain. All of his Genetics and Genome-wide association study, Single-nucleotide polymorphism, Gene, Genome and Expression quantitative trait loci investigations are sub-components of the entire Genetics study. His Selection research incorporates elements of Heritability, Animal breeding and Plant breeding.
As a member of one scientific family, Ben J. Hayes mostly works in the field of Quantitative trait locus, focusing on Linkage disequilibrium and, on occasion, Genetic diversity. His Genetic variation research includes themes of Candidate gene, SNP genotyping, Best linear unbiased prediction, Genomics and Genetic architecture. As part of the same scientific family, Ben J. Hayes usually focuses on Genetic gain, concentrating on Biotechnology and intersecting with Genomic selection and Dairy cattle.
Ben J. Hayes spends much of his time researching Genetic gain, Selection, Quantitative trait locus, Plant breeding and Genetic diversity. His study in Selection is interdisciplinary in nature, drawing from both Breeding program, Agronomy and Heritability. Ben J. Hayes focuses mostly in the field of Quantitative trait locus, narrowing it down to matters related to Expression quantitative trait loci and, in some cases, Gene expression, DNA microarray, RNA splicing and Exon.
His studies deal with areas such as Biotechnology, Food security and Crop as well as Plant breeding. His Genome research is within the category of Genetics. Ben J. Hayes is involved in the study of Genetics that focuses on Single-nucleotide polymorphism in particular.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps
T. H. E. Meuwissen;B. J. Hayes;M. E. Goddard.
Genetics (2001)
Invited review: Genomic selection in dairy cattle: progress and challenges.
B.J. Hayes;P.J. Bowman;A.J. Chamberlain;M.E. Goddard.
Journal of Dairy Science (2009)
Mapping genes for complex traits in domestic animals and their use in breeding programmes
Michael. Goddard;Ben John. Hayes.
Nature Reviews Genetics (2009)
Genome-Wide Survey of SNP Variation Uncovers the Genetic Structure of Cattle Breeds
Richard A. Gibbs;Jeremy F. Taylor;Curtis P. Van Tassell.
Science (2009)
Genome-wide analysis of the world's sheep breeds reveals high levels of historic mixture and strong recent selection.
James W. Kijas;Johannes A. Lenstra;Ben Hayes;Simon Boitard.
PLOS Biology (2012)
Whole-genome sequencing of 234 bulls facilitates mapping of monogenic and complex traits in cattle
Hans D Daetwyler;Aurélien Capitan;Hubert Pausch;Paul Stothard.
Nature Genetics (2014)
Pitfalls of predicting complex traits from SNPs
Naomi R. Wray;Jian Yang;Ben J. Hayes;Ben J. Hayes;Alkes L. Price.
Nature Reviews Genetics (2013)
Increased accuracy of artificial selection by using the realized relationship matrix
B. J. Hayes;P. M. Visscher;M. E. Goddard.
Genetics Research (2009)
Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels
M. Erbe;B.J. Hayes;B.J. Hayes;L.K. Matukumalli;S. Goswami.
Journal of Dairy Science (2012)
Linkage disequilibrium and persistence of phase in Holstein-Friesian, Jersey and Angus cattle
A. P. W. De Roos;Ben John. Hayes;R. Spelman;M. E. Goddard.
Genetics (2008)
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