• 한국미생물학회:학술대회논문집
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• 한국미생물학회 2008년도 International Meeting of the Microbiological Society of Korea
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• pp.147-149
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• 2008

• Genomics & Informatics
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• 제8권2호
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• pp.63-69
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• 2010

Monofunctional biosynthetic peptidoglycan transglycosylase (MBPT) catalyzes the formation of the glycan chain in bacterial cell walls from peptidoglycan subunits: N-acetylglucosamine (NAG) and acetylmuramic acid (NAM). Bifunctional glycosyltransferases such as the penicillin binding protein (PBP) have peptidoglycan glycosyltransferase (PGT) on their C terminal end which links together the peptidoglycan subunits while transpeptidase (TP) on the N terminal end cross-links the peptide moieties on the NAM monosaccharide of the peptide subunits to create the bacterial cell wall. The singular function of MBPT resembles the C terminal end of PBP as it too contains and utilizes a similar PGT domain. In this article we analyzed the infectious and non infectious protein sequences of MBPT from 31 different strains of bacteria using a variety of bioinformatic tools. Motif analysis, dot-plot comparison, and phylogenetic analysis identified a number of significant differences between infectious and non-infectious protein sequences. In this paper we have made an attempt to explain, analyze and discuss these differences from an evolutionary perspective. The results of our sequence analysis may open the door for utilizing MBPT as a new target to fight a variety of infectious bacteria.

• 한국자기공명학회논문지
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• 제13권2호
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• pp.108-116
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• 2009

The HP0902, a homodimeric 22.1 kDa protein, has been suggested as a putative secretory protein from Helicobacter pylori, although the protein possesses no signal peptide for secretion. Since it may be associated with the virulence of the bacterium, NMR study has been initiated in terms of structural genomics. In our previous effort to assign the backbone NMR resonances, using 800MHz NMR machine at pH 7.8, the resonances from eight of the 99 residues could not be assined due to missing of the signals. In this work, to enhance the extent of assignments, a 900 MHz machine was employed and the sample pH was reduced down to 6.5. Finally, almost all signals, except for those from G9 and S24, could be clearly assigned. The determined secondary structure using the assined chemical shifts indicated that the HP0902 consists of 11 ${\beta}$-strands with no helices. In our database search result, HP0902 was predicted to interact with VacA (Vacuolating cytotoxin A), which is a representative virulence factor secreted from Helicobacter pylori. Thus, molecular interaction between HP0902 and VacA would be worthy of investigation, on the basis of the present results of NMR assignments.

• 한국육종학회지
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• 제42권4호
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• pp.397-406
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• 2010

멜론과 참외의 국내 소비 시장이 확대됨에 따라 다양한 $F_1$ 품종이 개발되고 있다. 멜론과 참외의 $F_1$ 품종의 순도를 검정하기 위해 포장재배 등의 순도검정법이 이용되고 있으나 시간과 노력이 매우 많이 소요되기 때문에 분자마커를 이용한 순도검정법의 개발이 필요하다. 본 연구에서는 멜론의 EST 염기정보로부터 30개의 SNP 프라이머 조합을 고안하여 멜론과 참외의 순도 검정을 위한 HRM분석방법을 개발하였다. 멜론 두 품종과 참외 한 품종의 양친 사이에 HRM 해리곡선의 다형성을 보이는 10개의 마커를 선발하였으며 순도검정 마커를 선발하기 위해 blind test를 실시하였다. Blind test와 HRM 유전형 분석 결과가 일치하였으며 MEL SNP 2번과 12 마커를 이용하여 '레드 퀸'과 '얼쓰 VIP'의 $F_1$ 501개 개체에 대해 순도검정을 실시하였다. HRM분석한 결과 모두 이형집합체로 나타나 100%의 순도를 보였다. 또한 HRM 방법을 이용하여 개발한 SNP 마커를 CAPS 마커로 전환하였다. CAPS 마커는 HRM 분석 마커와 비교하여 볼 때 멜론과 참외의 순도검정용 마커로 더 유용하게 활용될 수 있을 것으로 기대된다.

• Genomics & Informatics
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• 제6권1호
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• pp.44-49
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• 2008

Protein kinase C (PKC) is a family of kinases involved in the transduction of cellular signals that promote lipid hydrolysis. PKC plays a pivotal role in mediating cellular responses to extracellular stimuli involved in proliferation, differentiation and apoptosis. Comparative analysis of the PKC-${\alpha},{\beta},{\varepsilon}$ isozymes of 200 recently sequenced microbial genomes was carried out using variety of bioinformatics tools. Diversity and evolution of PKC was determined by sequence alignment. The ser/thr protein kinases of Streptomyces coelicolor A3 (2), is the only bacteria to show sequence alignment score greater than 30% with all the three PKC isotypes in the sequence alignment. S.coelicolor is the subject of our interest because it is notable for the production of pharmaceutically useful compounds including anti-tumor agents, immunosupressants and over two-thirds of all natural antibiotics currently available. The comparative analysis of three human isotypes of PKC and Serine/threonine protein kinase of S.coelicolor was carried out and possible mechanism of action of PKC was derived. Our analysis indicates that Serine/ threonine protein kinase from S. coelicolor can be a good candidate for potent anti-tumor agent. The presence of three representative isotypes of the PKC super family in this organism helps us to understand the mechanism of PKC from evolutionary perspective.

• Genomics & Informatics
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• 제17권2호
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• pp.15.1-15.7
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• 2019

Automatically detecting mentions of pharmaceutical drugs and chemical substances is key for the subsequent extraction of relations of chemicals with other biomedical entities such as genes, proteins, diseases, adverse reactions or symptoms. The identification of drug mentions is also a prior step for complex event types such as drug dosage recognition, duration of medical treatments or drug repurposing. Formally, this task is known as named entity recognition (NER), meaning automatically identifying mentions of predefined entities of interest in running text. In the domain of medical texts, for chemical entity recognition (CER), techniques based on hand-crafted rules and graph-based models can provide adequate performance. In the recent years, the field of natural language processing has mainly pivoted to deep learning and state-of-the-art results for most tasks involving natural language are usually obtained with artificial neural networks. Competitive resources for drug name recognition in English medical texts are already available and heavily used, while for other languages such as Spanish these tools, although clearly needed were missing. In this work, we adapt an existing neural NER system, NeuroNER, to the particular domain of Spanish clinical case texts, and extend the neural network to be able to take into account additional features apart from the plain text. NeuroNER can be considered a competitive baseline system for Spanish drug and CER promoted by the Spanish national plan for the advancement of language technologies (Plan TL).

• Molecules and Cells
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• 제27권1호
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• pp.67-74
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• 2009

Autophagy degrades toxic materials and old organelles, and recycles nutrients in eukaryotic cells. Whereas the studies on autophagy have been reported in other eukaryotic cells, its functioning in plants has not been well elucidated. We analyzed the roles of OsATG10 genes, which are autophagy-related. Two rice ATG10 genes - OsATG10a and OsATG10b - share significant sequence homology (about 75%), and were ubiquitously expressed in all organs examined here. GUS assay indicated that OsATG10b was highly expressed in the mesophyll cells and vascular tissue of younger leaves, but its level of expression decreased in older leaves. We identified T-DNA insertional mutants in that gene. Those osatg10b mutants were sensitive to treatments with high salt and methyl viologen (MV). Monodansylcadaverine-staining experiments showed that the number of autophagosomes was significantly decreased in the mutants compared with the WT. Furthermore, the amount of oxidized proteins increased in MV-treated mutant seedlings. These results demonstrate that OsATG10b plays an important role in the survival of rice cells against oxidative stresses.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2000년도 International Symposium on Bioinformatics
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• pp.56-58
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• 2000

Post-genomics may be defined in different ways depending on how one views the challenges after the genome. A popular view is to follow the concept of the central dogma in molecular biology, namely from genome to transcriptome to proteome. Projects are going on to analyze gene expression profiles both at the mRNA and protein levels and to catalog protein 3D structure families, which will no doubt help the understanding of information in the genome. However complete, such catalogs of genes, RNAs, and proteins only tell us about the building blocks of life. They do not tell us much about the wiring (interaction) of building blocks, which is essential for uncovering systemic functional behaviors of the cell or the organism. Thus, an alternative view of post-genomics is to go up from the molecular level to the cellular level, and to understand, what I call, the "interactome"or a complete picture of molecular interactions in the cell. KEGG (http://www.genome.ad.jp/kegg/) is our attempt to computerize current knowledge on various cellular processes as a collection of "generalized"protein-protein interaction networks, to develop new graph-based algorithms for predicting such networks from the genome information, and to actually reconstruct the interactomes for all the completely sequenced genomes and some partial genomes. During the reconstruction process, it becomes readily apparent that certain pathways and molecular complexes are present or absent in each organism, indicating modular structures of the interactome. In addition, the reconstruction uncovers missing components in an otherwise complete pathway or complex, which may result from misannotation of the genome or misrepresentation of the KEGG pathway. When combined with additional experimental data on protein-protein interactions, such as by yeast two-hybrid systems, the reconstruction possibly uncovers unknown partners for a particular pathway or complex. Thus, the reconstruction is tightly coupled with the annotation of individual genes, which is maintained in the GENES database in KEGG. We are also trying to expand our literature surrey to include in the GENES database most up-to-date information about gene functions.

• 한국미생물생명공학회:학술대회논문집
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• 한국미생물생명공학회 2001년도 Proceedings of 2001 International Symposium
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• pp.15-19
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• 2001

Creating an artificial strain with a minimal gene set for a specific purpose is every biologist's dream. With the complete genome sequencing of more than 50 microorganisms and extensive functional analyses of their genes, it is possible to design a genetic blueprint for a simple custom-designed microbe with the minimal gene set. Two different approaches are being considered. The first 'top-down' approach is trimming the genome to a minimal gene set by selectively removing genes of an organism thought to be unnecessary based on microbial genomics. The second 'bottom-up' approach is to synthesize the proposed minimal genome from basic chemical building blocks. The 'top-down' approach starting with the genome of a well known microorganism is more technically feasible, whereas the bottom-up approach may not be attainable in the nearest future because of the lack of the complete functional analysis of the genes needed for a life. Here in this study, we used the top-down approach to minimize the E. coli genome to create an artificial organism with 'core' elements for self-sustaining and self-replicating cells by eliminating unnecessary genes. Using several different kinds of sophisticated deletion techniques combined with a p:1age and transposons, we deleted about 19％ of the E. coli genome without causing any damages to cellular growth. This smaller E. coli genome will be further reduced to a genome with a minimal gene l;et essential for cell life. This minimized E. coli genome can lead to the construction of many custom-designed strains with myriad practical and commercial applications.

• 디지털콘텐츠학회 논문지
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• 제11권1호
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• pp.99-104
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• 2010

화학물질은 생체에 들어오면 여러 가지 독성반응을 나타내는데, 독성반응에 따른 유전자 발현을 분석하기 위해 바이오 칩 등을 이용한 신기술이 확산되면서 바이오 디지털 콘텐츠가 다량으로 생성되고 있다. 이 콘텐츠는 그 자체로는 의미가 적고 컴퓨터를 이용한 분석과 보정과정을 거쳐 생물학적으로 의미 있는 값들을 선별하여야 한다. 이런 콘텐츠에는 유전자들의 발현 양상 측정을 목적으로 하는 유전체학(genomics), 유전자의 발현 양상을 측정하는 전사체학(transcriptomics), 단백질의 발현을 측정하는 단백체학(proteomics), 대사체의 발현을 측정하는 대사체학(metabolomics) 등이 있으며, 이를 통칭하여 오믹스(omics)라고 부른다. 오믹스 기술을 독성을 연구하는 분야에 접목한 것이 독성유전체학(toxicogenomics)이며, 이에 대한 콘텐츠를 분석함으로써 독성을 예측하고 독성기전을 규명할 수 있다. 독성분석에 있어서 초기 단계의 분석은 향후 만성독성의 예측에 있어서 중요한 부분을 차지하고 있다. 바이오 디지털 콘텐츠를 이용하여 독성을 예측함에 있어 기존의 방법보다 더 빠르고 정확하게 예측하기 위해서는 많은 정보에 대한 분석기술의 진보가 필요하다. 또, 바이오 디지털 콘텐츠를 이용한 독성예측에 있어서 전체세포보다는 생물학적 현상을 일으키는 특이세포에서 이런 정보를 얻는 것이 중요하다고 생각된다. 또, 향후 바이오 디지털 콘텐츠 분석은 전략적 실험설계에 의한 데이터가 분석되고 축적되어야 하고, 분석알고리즘을 통한 네트워크 분석이 이루어져야 하며, 통합적 데이터 구축을 통해 이루어져야 할 것으로 생각된다.