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Solomon Antwi Boison

Researcher at University of Natural Resources and Life Sciences, Vienna

Publications -  32
Citations -  464

Solomon Antwi Boison is an academic researcher from University of Natural Resources and Life Sciences, Vienna. The author has contributed to research in topics: Population & Quantitative trait locus. The author has an hindex of 11, co-authored 28 publications receiving 348 citations.

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Accuracy of genotype imputation in Nelore cattle

TL;DR: If the Illumina® BovineHD is considered as the target chip for genomic applications in the Nelore breed, cost-effectiveness can be improved by genotyping part of the animals with a chip containing around 15 K useful SNPs and imputing their high-density missing genotypes with FImpute.
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Genomic analysis for managing small and endangered populations: a case study in Tyrol Grey cattle

TL;DR: The objective of the paper was to demonstrate how genomic data could be used to analyse linkage disequlibrium, LD decay and the effective population size, and prediction of genomic breeding values (GEBV) using small within-breed and genomic information from other breeds.
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Strategies for single nucleotide polymorphism (SNP) genotyping to enhance genotype imputation in Gyr (Bos indicus) dairy cattle: Comparison of commercially available SNP chips.

TL;DR: Investigation of strategies and factors affecting the accuracy of genotype imputation in Gyr (Bos indicus) dairy cattle found that a genotyping strategy that uses the HD-777K SNP chip as a reference panel and SGGP-20Ki as the lower-density SNP panel should be adopted as accuracy was high and similar to that of the 50K.
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Genomic and Transcriptomic Analysis of Amoebic Gill Disease Resistance in Atlantic Salmon (Salmo salar L.)

TL;DR: The molecular signatures of AGD infection in Atlantic salmon through a challenge model and genome-wide association analysis found QTL regions on chromosomes ssa04, ssa09, and ssa13 were detected to be linked with AGD resistance, suggesting thousands of genes have modified their expression following infection.