• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.45-52
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• 2000

Genomic approach produces massive amount of data within a short time period, New high-throughput automatic sequencers can generate over a million nucleotide sequence information overnight. A typical DNA chip experiment produces tens of thousands expression information, not to mention the tens of megabyte image files, These data must be handled automatically by computer and stored in electronic database, Thus there is a need for systematic approach of data collection, processing, and analysis. DNA sequence information is translated into amino acid sequence and is analyzed for key motif related to its biological and/or biochemical function. Functional genomics will play a significant role in identifying novel drug targets and diagnostic markers for serious diseases. As an enabling technology for functional genomics, bioinformatics is in great need worldwide, In Korea, a new functional genomics project has been recently launched and it focuses on identi☞ing genes associated with cancers prevalent in Korea, namely gastric and hepatic cancers, This involves gene discovery by high throughput sequencing of cancer cDNA libraries, gene expression profiling by DNA microarray and proteomics, and SNP profiling in Korea patient population, Our bioinformatics team will support all these activities by collecting, processing and analyzing these data.

• Korean Journal of Environmental Biology
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• v.30 no.2
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• pp.77-89
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• 2012

With the advent of the genomics era powered by DNA sequencing technologies, life science is being transformed significantly and biological research and development have been accelerated. Environmental biology concerns the relationships among living organisms and their natural environment, which constitute the global biogeochemical cycle. As sustainability of the ecosystems depends on biodiversity, examining the structure and dynamics of the biotic constituents and fully grasping their genetic and metabolic capabilities are pivotal. The high-speed high-throughput next-generation sequencing can be applied to barcoding organisms either thriving or endangered and to decoding the whole genome information. Furthermore, diversity and the full gene complement of a microbial community can be elucidated and monitored through metagenomic approaches. With regard to human welfare, microbiomes of various human habitats such as gut, skin, mouth, stomach, and vagina, have been and are being scrutinized. To keep pace with the rapid increase of the sequencing capacity, various bioinformatic algorithms and software tools that even utilize supercomputers and cloud computing are being developed for processing and storage of massive data sets. Environmental genomics will be the major force in understanding the structure and function of ecosystems in nature as well as preserving, remediating, and bioprospecting them.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.04a
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• pp.5-5
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• 2018

Ginseng (Panax ginseng C.A. Meyer), one of the most widely used medicinal plants in traditional oriental medicine, is used for the treatment of various diseases. It has been classified according to its cultivation environment, such as field cultivated ginseng (FCG) and mountain cultivated ginseng (MCG). However, little is known about differences in gene expression in ginseng roots between field cultivated and mountain cultivated ginseng. In order to investigate the whole transcriptome landscape of ginseng, we employed High-Throughput sequencing technologies using the Illumina HiSeqTM2500 system, and generated a large amount of sequenced transcriptome from ginseng roots. Approximately 77 million and 87 million high-quality reads were produced in the FCG and MCG roots transcriptome analyses, respectively, and we obtained 256,032 assembled unigenes with an average length of 1,171 bp by de novo assembly methods. Functional annotations of the unigenes were performed using sequence similarity comparisons against the following databases: the non-redundant nucleotide database, the InterPro domains database, the Gene Ontology Consortium database, and the Kyoto Encyclopedia of Genes and Genomes pathway database. A total of 4,207 unigenes were assigned to specific metabolic pathways, and all of the known enzymes involved in starch and sucrose metabolism pathways were also identified in the KEGG library. This study indicated that alpha-glucan phosphorylase 1, putative pectinesterase/pectinesterase inhibitor 17, beta-amylase, and alpha-glucan phosphorylase isozyme H might be important factors involved in starch and sucrose metabolism between FCG and MCG in different environments.

• Genomics & Informatics
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• v.11 no.3
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• pp.102-113
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• 2013

Metagenomics has become one of the indispensable tools in microbial ecology for the last few decades, and a new revolution in metagenomic studies is now about to begin, with the help of recent advances of sequencing techniques. The massive data production and substantial cost reduction in next-generation sequencing have led to the rapid growth of metagenomic research both quantitatively and qualitatively. It is evident that metagenomics will be a standard tool for studying the diversity and function of microbes in the near future, as fingerprinting methods did previously. As the speed of data accumulation is accelerating, bioinformatic tools and associated databases for handling those datasets have become more urgent and necessary. To facilitate the bioinformatics analysis of metagenomic data, we review some recent tools and databases that are used widely in this field and give insights into the current challenges and future of metagenomics from a bioinformatics perspective.

• Journal of Genetic Medicine
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• v.15 no.2
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• pp.110-114
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• 2018

Ataxia-telangiectasia (AT; OMIM 208900) is a rare autosomal recessive inherited progressive neurodegenerative disorder, with onset in early childhood. AT is caused by homozygous or compound heterozygous mutations in ATM (OMIM 607585) on chromosome 11q22. The average prevalence of the disease is estimated at 1 of 100,000 children worldwide. The prevalence of AT in the Republic of Korea is suggested to be extremely low, with only a few cases genetically confirmed thus far. Herein, we report a 5-year-old Korean boy with clinical features such as progressive gait and truncal ataxia, both ankle spasticity, dysarthria, and mild intellectual disability. The patient was identified as a compound heterozygote with two novel genetic variants: a paternally derived c.5288_5289insGA p.(Tyr1763*) nonsense variant and a maternally derived c.8363A>C p.(His2788Pro) missense variant, as revealed by next-generation sequencing and confirmed by Sanger sequencing. Based on claims data from the Health Insurance Review and Assessment Service Republic of Korea, we calculated the prevalence of AT in the Republic of Korea to be about 0.9 per million individuals, which is similar to the worldwide average. Therefore, we suggest that multi-gene panel sequencing including ATM should be considered early diagnosis.

• Genomics & Informatics
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• v.16 no.4
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• pp.36.1-36.3
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• 2018

Next generation sequencing (NGS), a high-throughput DNA sequencing technology, is widely used for molecular biological studies. In NGS, RNA-sequencing (RNA-Seq), which is a short-read massively parallel sequencing, is a major quantitative transcriptome tool for different transcriptome studies. To utilize the RNA-Seq data, various quantification and analysis methods have been developed to solve specific research goals, including identification of differentially expressed genes and detection of novel transcripts. Because of the accumulation of RNA-Seq data in the public databases, there is a demand for integrative analysis. However, the available RNA-Seq data are stored in different formats such as read count, transcripts per million, and fragments per kilobase million. This hinders the integrative analysis of the RNA-Seq data. To solve this problem, we have developed a web-based application using Shiny, COEX-seq (Convert a Variety of Measurements of Gene Expression in RNA-Seq) that easily converts data in a variety of measurement formats of gene expression used in most bioinformatic tools for RNA-Seq. It provides a workflow that includes loading data set, selecting measurement formats of gene expression, and identifying gene names. COEX-seq is freely available for academic purposes and can be run on Windows, Mac OS, and Linux operating systems. Source code, sample data sets, and supplementary documentation are available as well.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.9
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• pp.1345-1352
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• 2016

The hindgut of horses is an anaerobic fermentative chamber for a complex and dynamic microbial population, which plays a critical role in health and energy requirements. Research on the gut microbiota of Mongolian horses has not been reported until now as far as we know. Mongolian horse is a major local breed in China. We performed high-throughput sequencing of the 16S rRNA genes V4 hypervariable regions from gut fecal material to characterize the gut microbiota of Mongolian horses and compare them to the microbiota in Thoroughbred horses. Fourteen Mongolian and 19 Thoroughbred horses were used in the study. A total of 593,678 sequence reads were obtained from 33 samples analyzed, which were found to belong to 16 phyla and 75 genera. The bacterial community compositions were similar for the two breeds. Firmicutes (56% in Mongolian horses and 53% in Thoroughbred horses) and Bacteroidetes (33% and 32% respectively) were the most abundant and predominant phyla followed by Spirochaete, Verrucomicrobia, Proteobacteria, and Fibrobacteres. Of these 16 phyla, five (Synergistetes, Planctomycetes, Proteobacteria, TM7, and Chloroflexi) were significantly different (p<0.05) between the two breeds. At the genus level, Treponema was the most abundant genus (43% in Mongolian horses vs 29% in Thoroughbred horses), followed by Ruminococcus, Roseburia, Pseudobutyrivibrio, and Anaeroplasma, which were detected in higher distribution proportion in Mongolian horses than in Thoroughbred horses. In contrast, Oscillibacter, Fibrobacter, Methanocorpusculum, and Succinivibrio levels were lower in Mongolian horses. Among 75 genera, 30 genera were significantly different (p<0.05) between the two breeds. We found that the environment was one of very important factors that influenced horse gut microbiota. These findings provide novel information about the gut microbiota of Mongolian horses and a foundation for future investigations of gut bacterial factors that may influence the development and progression of gastrointestinal disease in horses.

• Korean Journal of Microbiology
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• v.54 no.3
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• pp.188-199
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• 2018

Genomic epidemiology exploits various basic microbial research areas. High-throughput sequencing technologies dramatically have been expanding the number of microbial genome sequences available. Abundant genomic data provide an opportunity to perform strain typing more effectively, helping identify microbial species and strains at a higher resolution than ever before. Genomic epidemiology needs to find antimicrobial resistance genes in addition to standard genome annotations. Strain typing and antimicrobial resistance gene finding are static aspects of genomic epidemiology. Finding which hosts infected which other hosts requires the inference of transient transmission routes among infected hosts. The strain typing, antimicrobial resistance gene finding, and transmission tree inference would allow for better surveillance of microbial infectious diseases, which is one of the ultimate goals of genomic epidemiology. Among several high-throughput sequencing technologies, genomic epidemiology will benefit from the more portability and shorter sequencing time of the Oxford Nanopore Technologies's MinION, the third-generation sequencing technology. Here, this study reviewed computational methods for quantifying antimicrobial resistance genes and inferring disease transmission trees. In addition, the MinION's applications to genomic epidemiology were discussed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.12 no.19
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• pp.79-88
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• 1989

This characteristics of process industries are high capital intensity, relatively long and sequence dependent setup times, and extremely limited capacity resources. The lot sizing, sequencing and limited capacity resources factors must he considered for production scheduling in these industries. This paper presents a mixed integer programming model for production scheduling. The economic trade offs between capacitated lot sizing flow shop scheduling and sequence dependent setup times also be compared with SMITH-DANIELS's model. As a results, it is shown that this paper has lower total cost, more efficient throughput than SMITH-DANIELS's model.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.10
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• pp.1456-1463
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• 2017

Objective: To investigate the effect of host genetics on gut microbial diversity, we performed a structural survey of the fecal microbiota of four purebred boar pig lines: Duroc, Landrace, Hampshire, and Yorkshire. Methods: The V3-V4 regions of the 16S rRNA genes were amplified and sequenced. Results: A total of 783 operational taxonomic units were shared by all breeds, whereas others were breed-specific. Firmicutes and Bacteroidetes dominated the majority of the fecal microbiota; Clostridia, Bacilli, and Bacteroidia were the major classes. Nine predominant genera were observed in all breeds and eight of them can produce short-chain fatty acids. Some bacteria can secrete cellulase to aid fiber digestion by the host. Butyric, isobutyric, valeric, and isovaleric acid levels were highest in Landrace pigs, whereas acetic and propionic acid were highest in the Hampshire breed. Heatmap was used to revealed breed-specific bacteria. Principal coordinate analysis of fecal bacteria revealed that the Landrace and Yorkshire breeds had high similarity and were clearly separated from the Duroc and Hampshire breeds. Conclusion: Overall, this study is the first time to compare the fecal microbiomes of four breeds of boar pig by high-throughput sequencing and to use Spearman's rank correlation to analyze competition and cooperation among the core bacteria.