• Korean Journal of Microbiology
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• v.54 no.3
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• pp.302-304
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• 2018

We, for the first time, isolated and identified a Vibrio splendidus KCTC 11899BP producing hyaluronate lyase from seawater. This enzyme is produced only when hyaluronic acid (HA) is added to the basal medium. Hyaluronate lyases are produced by microorganisms, which degrade the ${\beta}$-(1, 4) bond of HA to produce disaccharide. The genome of KCTC 11899BP, which consist of two circular contigs that are 3,522 kb (contig 1) long and 1,986 kb (contig 2) long respectively, as like other Vibrio sp. that contained 2 chromosomes. The genome included 4,700 predicted open reading frames, G + C content 44.12%, 137 tRNA genes, and 46 rRNA genes.

• Journal of Microbiology and Biotechnology
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• v.28 no.4
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• pp.561-565
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• 2018

The late-stage doxorubicin biosynthesis pathway acting enzyme (DoxA) from Streptomyces peucetius CYP129A2 exhibited substrate promiscuity towards the stilbene group of compounds such as resveratrol. DoxA along with two accessory enzymes ferrdoxin reductase and ferredoxin from spinach hydroxylated resveratrol at the 3'-position in vitro to produce piceatannol. The product was identified by HPLC-PDA and high-resolution HR-qTOF-ESI/MS analyses in positive mode. The ESI/MS fragments resembled the hydroxylated product of resveratrol.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.13-20
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• 2004

Grid system has the potential to resolve the current need of bioinformatics for super-computing environment inexpensively. There are already several Grid applications of bioinformatics tools. To solve the real-world bioinformatics problems, however, the various integration of each tool is necessary in addition to the implementation of more basic tools. Workflow based problem solving environment can be the efficient solution for this type of software development. There are still heavy overhead, however, to develop and implement workflow model on current Grid system. He re we propose a model of simple problem solving environment that enables component based workflow design of integrated bioinformatics applications on Grid environment by using Condor functionalities. We realized this model for practical bioinformatics solutions of a genome sequence analysis and a comparative genome analysis. We implemented necessary bioinformatics tools and interfacing tools as the components, and combine them in the workflow model of each solution by using the tools presented in Condor.

• Genomics & Informatics
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• v.17 no.3
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• pp.25.1-25.6
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• 2019

Genomics & Informatics (NLM title abbreviation: Genomics Inform) is the official journal of the Korea Genome Organization. Herein, we conduct a statistical analysis of the publications of Genomics & Informatics over the 16 years since its inception, with a particular focus on issues relating to article categories, word clouds, and the most-studied genes, drawing on recent reviews of the use of word frequencies in journal articles. Trends in the studies published in Genomics & Informatics are discussed both individually and collectively.

• Journal of Life Science
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• v.29 no.1
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• pp.123-128
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• 2019

The use of 16S rDNA is commonplace in the determination of prokaryotic species. However, it has limitations, and there are few studies at the genus level. We investigated conserved genes and metabolic pathways at the genus level in 28 strains of 13 genera of prokaryotes using the COG database (conserved genes) and MetaCyc database (metabolic pathways). Conserved genes compared to total genes (core genome) at the genus level ranged from 27.62%(Nostoc genus) to 71.76%(Spiribacter genus), with an average of 46.72%. The lower ratio of core genome meant the higher ratio of peculiar genes of a prokaryote, namely specific biological activities or the habitat may be varied. The ratio of common metabolic pathways at the genus level was higher than the ratio of core genomes, from 58.79% (Clostridium genus) to 96.31%(Mycoplasma genus), with an average of 75.86%. When compared among other genera, members of the same genus were positioned in the closest nodes to each other. Interestingly, Bacillus and Clostridium genera were positioned in closer nodes than those of the other genera. Archaebacterial genera were grouped together in the ortholog and metabolic pathway nodes in a phylogenetic tree. The genera Granulicella, Nostoc, and Bradyrhizobium of the Acidobacteria, Cyanobacteria, and Proteobacteria phyla, respectively, were grouped in an ortholog content tree. The results of this study can be used for (i) the identification of common genes and metabolic pathways at each phylogenetic level and (ii) the improvement of strains through horizontal gene transfer or site-directed mutagenesis.

• Genomics & Informatics
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• v.6 no.4
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• pp.173-180
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• 2008

The human genome has evolved as a consequence of evolutionary forces, such as natural selection. In this study, we investigated natural selection on the human genes by comparing the numbers of nonsynonymous (NS) and synonymous (S) mutations in individual genes. We initially collected all coding SNP data of all human genes from the public dbSNP. Among the human genes, we selected 3 different selection groups of genes: positively selected genes (NS/S${\geq}$3), negatively selected genes (NS/S${\leq}$1/3) and neutral selection genes (0.9

• Journal of Digital Convergence
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• v.14 no.4
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• pp.349-353
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• 2016

The studies on the human environment and ecosystem analysis is being actively researched. In recent years, The service of genome analysis has been offering the customized service to prevent the disease as reading an individual's genome information. The genome information by analyzing technology is being required accurate and fast analyses of ecosystem-dielectrics due to the spread of the disease, the use of genetically modified organism and the influx of exotic. In this paper the algorithm of K-Mean clustering for a new classification system was utilized. It will provide new dielectrics information as quickly and accurately for many biologists.

• Genomics & Informatics
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• v.7 no.2
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• pp.57-64
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• 2009

Fibrinogen alpha chain (FGA), a subunit of fibrinogen, might be a potential player for type 2 diabetes mellitus (T2DM), since the plasma levels of fibrinogen is known to be related to the incidence of T2DM. To elucidate the potential role of FGA in T2DM, we investigated whether FGA genetic variations are relevant in T2DM in the Korean population. Seven FGA single nucleotide polymorphisms (SNPs) were genotyped in Ansung and Ansan cohorts (474 T2DM subjects and 470 normal controls) in Korea. The association between SNPs and T2DM was determined by logistic regression analysis. Genetic relevance of SNPs to T2DM-related phenotypes was investigated by multiple linear regression analysis. Statistical analysis revealed that among seven FGA SNPs, significant associations with T2DM were observed in FGA rs2070011 (p=0.013-0.034, OR=0.72${\sim}$0.79), rs6050 (p=0.026${\sim}$0.048, OR=1.24${\sim}$1.37), and rs2070022 (p=0.016${\sim}$0.039, OR=0.70${\sim}$0.72). Two SNPs, rs2070011 and rs6050, also showed significant association with T2DM-related phenotypes such as triglyceride (p=0.005${\sim}$0.011 for rs2070011 and p=0.003${\sim}$0.008 for rs6050), total cholesterol (p=0.01 for rs2070011 and p=0.024 for rs6050) and fasting glucose (p=0.035${\sim}$0.036 for rs2070011 and p=0.048 for rs6050) in 470 normal controls. Our association study implies that FGA might be an important genetic factor in T2DM pathogenesis in the Korean population by affecting plasma lipid and glucose levels.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.2
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• pp.97-106
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• 2013

Since human genome project finished, the cost for human genome analysis has decreased very rapidly. This results in the sharp increase of human genome data to be analyzed. As the need for fast analysis of very large bio data such as human genome increases, non IT researchers such as biologists should be able to execute fast and effectively many kinds of bio applications, which have a variety of characteristics, under HPC environment. To accomplish this purpose, a biologist need to define a sequence of bio applications as workflow easily because generally bio applications should be combined and executed in some order. This bio workflow should be executed in the form of distributed and parallel computing by allocating computing resources efficiently under HPC cluster system. Through this kind of job, we can expect better performance and fast response time of very large bio data analysis. This paper proposes a workflow-based data analysis system specialized for bio applications. Using this system, non-IT scientists and researchers can analyze very large bio data easily under HPC environment.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.13-16
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• 2000

Microorganisms have been widely employed for the production of useful bioproducts including primary metabolites such as ethanol, succinic acid, acetone and butanol, secondary metabolites represented by antibiotics, proteins, polysaccharides, lipids and many others. Since these products can be obtained in small quantities under natural condition, mutation and selection processes have been employed for the improvement of strains. Recently, metabolic engineering strategies have been employed for more efficient production of these bioproducts. Metabolic engineering can be defined as purposeful modification of cellular metabolic pathways by introducing new pathways, deleting or modifying the existing pathways for the enhanced production of a desired product or modified/new product, degradation of xenobiotics, and utilization of inexpensive raw materials. Metabolic flux analysis and metabolic control analysis along with recombinant DNA techniques are three important components in designing optimized metabolic pathways, This powerful technology is being further improved by the genomics, proteomics, metabolomics and bioinformatics. Complete genome sequences are providing us with the possibility of addressing complex biological questions including metabolic control, regulation and flux. In silico analysis of microbial metabolic pathways is possible from the completed genome sequences. Transcriptome analysis by employing ONA chip allows us to examine the global pattern of gene expression at mRNA level. Two dimensional gel electrophoresis of cellular proteins can be used to examine the global proteome content, which provides us with the information on gene expression at protein level. Bioinformatics can help us to understand the results obtained with these new techniques, and further provides us with a wide range of information contained in the genome sequences. The strategies taken in our lab for the production of pharmaceutical proteins, polyhydroxyalkanoate (a family of completely biodegradable polymer), succinic acid and me chemicals by employing metabolic engineering powered by genomics, proteomics, metabolomics and bioinformatics will be presented.