Publications by authors named "Woon-Young Hong"

Background: The use of whole genome sequence has increased recently with rapid progression of next-generation sequencing (NGS) technologies. However, storing raw sequence reads to perform large-scale genome analysis pose hardware challenges. Despite advancement in genome analytic platforms, efficient approaches remain relevant especially as applied to the human genome.

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Calling variants from next-generation sequencing (NGS) data or discovering discordant sequences between two NGS data sets is challenging. We developed a computer algorithm, ADIScan1, to call variants by comparing the fractions of allelic reads in a tester to the universal reference genome. We then created ADIScan2 by modifying the algorithm to directly compare two sets of NGS data and predict discordant sequences between two testers.

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Advances in next generation sequencing (NGS) technologies have enabled population-level studies for many animals to unravel the relationships between genotypic differences and traits of specific populations. The objective of this study was to perform evolutionary analysis of single nucleotide polymorphisms (SNP) in genes of Korean native cattle Hanwoo in comparison to SNP data from four other cattle breeds (Jersey, Simmental, Angus, and Holstein) and four related species (pig, horse, human, and mouse) obtained from public databases through NGS-based resequencing. We analyzed population structures and differentiation levels for the five cattle breeds and estimated species-specific SNPs with their origins and phylogenetic relationships among species.

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Recent advances in next-generation sequencing technologies and genome assembly algorithms have enabled the accumulation of a huge volume of genome sequences from various species. This has provided new opportunities for large-scale comparative genomics studies. Identifying and utilizing synteny blocks, which are genomic regions conserved among multiple species, is key to understanding genomic architecture and the evolutionary history of genomes.

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Next-generation sequencing (NGS) technologies make it possible to obtain the entire genomic content of microorganisms in metagenome samples. Thus, many studies have developed methods for the processing and analysis of metagenomic NGS reads, including analyses for predicting functions and their enrichments in environmental metagenome samples. Especially, comparative functional studies by using multi-metagenome samples are essential for identifying and comparing different characteristics of multiple environmental samples.

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