• Proceedings of the Korean Society of Crop Science Conference
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• 2020.06a
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• pp.170-170
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• 2020

• Genomics & Informatics
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• v.2 no.1
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• pp.53-56
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• 2004

• Molecules and Cells
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• v.23 no.2
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• pp.170-174
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• 2007

High-throughput subcellular imaging is a powerful tool for investigating the function of genes. In order to identify novel regulators of apoptosis we transiently transfected HeLa cells with 938 hypothetical genes of unknown function, and captured their nuclear images with an automated fluorescence microscope. We selected genes that induced greater than 3-fold increase in the percentage of apoptotic nuclei compared with vector-transfected cells. The full-length genes C10orf61, MGC 26717, and FLJ13855 were identified as candidate proapoptotic genes, and their apoptotic effects were confirmed by DNA fragmentation ELISAs and Western blotting for caspase-7 and PARP. We conclude that a subcellular image-based apoptotic screen is useful for identifying genes with proapoptotic activity.

• The Korea Genome Conference
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• 2004.07a
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• pp.35.1-35.1
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• 2004

• Proceedings of the Korea Crystallographic Association Conference
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• 2003.05a
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• pp.15-15
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• 2003

To discover new drugs more quickly and more efficiently, pharmaceutical companies and biotechnology firms are increasingly turning to the genomics and the structural proteomics technologies. Structural-proteomics can provide a foundation for this through the determination and analysis for protein structure on a genomics scale. Among many structures determined by CGI, we will present with the representative examples drawn from our work on novel structures or complex structures of the disease-related proteins. The alpha subunit of Hypoxia-inducible factor (HIF) is targeted for degradation under normoxic conditions by an ubiquitin-ligase complex that recognizes a hydroxylated proline residue in HIF. Hydroxylation is catalysed by HIF prolyl 4-hydroxylases (HIFPH) which are fe(II) and 2-oxoglutarate (2-OG) dependent oxygenases. Here, we discuss the first crystal structure of the catalytic domain of HIFPH in complexes, with the Fe(II)/2-OG at 1.8Å. These structures suggest that the Ll region (residues 236-253), which is also conserved in mammals, form a 'lid' that closes over the active site. The structural and mutagenesis analyses allow us to provide a focus for understanding cellular responses to hypoxia and a target for the therapeutic manipulation.

• Proceedings of the Korean Biophysical Society Conference
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• 2003.06a
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• pp.28-28
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• 2003

To discover new drugs more quickly and more efficiently, pharmaceutical companies and biotechnology firms are increasingly turning to the genomics and the structural proteomics technologies. Structural-proteomics can provide a foundation for this through the determination and analysis for protein structure on a genomics scale. Among many structures determined by CGI, we will present with the representative examples drawn from our work on novel structures or complex structures of the disease-related proteins. The alpha subunit of Hypoxia-inducible factor (HIF) is targeted for degradation under normoxic conditions by an ubiquitin-ligase complex that recognizes a hydroxylated proline residue in HIF, Hydroxylation is catalysed by HIF prolyl 4-hydroxylases (HIFPH) which are Fe(II) and 2-oxoglutarate (2-OG) dependent oxygenases. Here, we discuss the first crystal structure of the catalytic domain of HIFPH in complexes, with the Fe(II)/2-OG at 1.8 ${\AA}$. These structures suggest that the L1 region (residues 236-253), which is also conserved in mammals, form a ‘lid’ that closes over the active site. The structural and mutagenesis analyses allow us to provide a focus for understanding cellular responses to hypoxia and a target for the therapeutic manipulation.

• Genomics & Informatics
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• v.11 no.4
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• pp.174-179
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• 2013

The large amount of data on cancer genome research has contributed to our understanding of cancer biology. Indeed, the genomics approach has a strong advantage for analyzing multi-factorial and complicated problems, such as cancer. It is time to think about the actual usage of cancer genomics in the clinical field. The clinical cancer field has lots of unmet needs in the management of cancer patients, which has been defined in the pre-genomic era. Unmet clinical needs are not well known to bioinformaticians and even non-clinician cancer scientists. A personalized approach in the clinical field will bring potential additional challenges to cancer genomics, because most data to now have been population-based rather than individualbased. We can maximize the use of cancer genomics in the clinical field if cancer scientists, bioinformaticians, and clinicians think and work together in solving unmet clinical needs. In this review, we present one imaginary case of a cancer patient, with which we can think about unmet clinical needs to solve with cancer genomics in the diagnosis, prediction of prognosis, monitoring the status of cancer, and personalized treatment decision.

• Genomics & Informatics
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• v.10 no.1
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• pp.33-39
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• 2012

High-throughput genomic technologies (HGTs), including next-generation DNA sequencing (NGS), microarray, and serial analysis of gene expression (SAGE), have become effective experimental tools for cancer genomics to identify cancer-associated somatic genomic alterations and genes. The main hurdle in cancer genomics is to identify the real causative mutations or genes out of many candidates from an HGT-based cancer genomic analysis. One useful approach is to refer to known cancer genes and associated information. The list of known cancer genes can be used to determine candidates of cancer driver mutations, while cancer gene-related information, including gene expression, protein-protein interaction, and pathways, can be useful for scoring novel candidates. Some cancer gene or mutation databases exist for this purpose, but few specialized tools exist for an automated analysis of a long gene list from an HGT-based cancer genomic analysis. This report presents a new web-accessible bioinformatic tool, called CaGe, a cancer genome annotation system for the assessment of candidates of cancer genes from HGT-based cancer genomics. The tool provides users with information on cancer-related genes, mutations, pathways, and associated annotations through annotation and browsing functions. With this tool, researchers can classify their candidate genes from cancer genome studies into either previously reported or novel categories of cancer genes and gain insight into underlying carcinogenic mechanisms through a pathway analysis. We show the usefulness of CaGe by assessing its performance in annotating somatic mutations from a published small cell lung cancer study.

• Molecular & Cellular Toxicology
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• v.2 no.4
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• pp.273-278
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• 2006

95 squamous cell lung carcinoma samples (normal tissue: 40 samples, tumor: 55 samples) were analyzed with 8 K cDNA microarray. 1-way ANOVA test was employed to select differentially expressed genes in tumor with FDR<0.01. Among the selected 1,655 genes, final 212 genes were chosen according to the expression fold change and used for following analysis. The expression of up-regulated 64 genes was verified with Reverse Transcription PCR and 10 genes were identified as candidates for SCC markers. In our opinion, those candidates can be exploited as diagnostic or therapeutic purposes. Gene Ontology (GO) based analysis was performed using those 212 genes, and following categories were revealed as significant biological processes: Immune response (GO: 0006955), antigen processing (GO: 0030333), inflammatory response (GO: 0006954), Cell adhesion (GO: 0007155), and Epidermis differentiation (GO: 0008544). Gene set enrichment analysis (GSEA) also carried out on overall gene expression profile with 522 functional gene sets. Glycolysis, cell cycle, K-ras and amino acid biosynthesis related gene sets were most distinguished. These results are consistent with the known characteristics of SCC and may be interconnected to rapid cell proliferation. However, the unexpected results from ERK activation in squamous cell carcinoma gripped our attention, and further studies are under progress.

• Food Science of Animal Resources
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• v.30 no.4
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• pp.655-660
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• 2010

This study aimed to identify genetic polymorphisms associated with fatty acid composition in Hanwoo beef. In this study, three SNPs (-867G>C, -877Gdel and 878T>C) were detected in SCD gene by DNA sequencing and PCR-RFLP. Statistical analysis revealed that 878T>C SNP was significantly associated with total saturated (p=0.016), unsaturated (p=0.016), and monounsaturated fatty acid (p=0.026) composition. However, the other two SNPs (-867G>C and -877Gdel) that are detected in the regulatory region of the SCD gene have no association with the fatty acid composition of Hanwoo meat. The 878C (alanine type) allele was found to be associated with 2.2% higher monounsaturated fatty acid, 1.5% lower saturated fatty acid, and 1.4% higher unsaturated fatty acid content than those associated with the 878T (valine type) allele. These results indicate that the non-synonymous SNP (878T>C) in the SCD gene could be a causal mutation that contributes to the MUFA variation in Hanwoo beef.