• 한국생물공학회:학술대회논문집
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• 2001.11a
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• pp.845-848
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• 2001

For understanding physiology and metabolism under various culture conditions, combined analysis of transcriptome and proteome is attractable way. We have manufactured DNA microarray containing 2,850 genes including all functionally known and putative ones. In this study, we report analysis of transcriptome and proteome during the high cell density culture of E. coli by using DNA microarray and 2-DE. Fed-batch fermentation of E. coli was carried out by exponential feeding of nutrients until the maximum cell density reached 74 g dry cell weight/L (g DCW/L). Changes in transcriptome and proteome during the HCDC are analyzed qualitatively and quantitatively to provide their physiological and metabolic meanings.

• Molecular & Cellular Toxicology
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• v.3 no.4
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• pp.282-291
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• 2007

Although the etiology of schizophrenia is known to be linked with the disturbance of glutamatergic and dopaminergic neurotransmission, little is known about the relationship between gene expression and the disease process. To identify genes related to abnormalities in glutamatergic and dopaminergic function, we investigated the effects of olanzapine in the changes of mRNA levels in the animal model of schizophrenia, using a high-density DNA microarray. Olanzapine (3.0 mg/kg, i.p.) significantly reduced hyperlocomotive activities, which was induced by MK-801 (1.0 mg/kg, i.p.). We identified that the expression of 719 genes were significantly altered more than two folds in the prefrontal cortex of the rats treated with MK-801. We selected 15 genes out of them by the changes of the expression pattern in the treatment of Olanzapine and/or MK801 for the further confirmation in RT-PCR. The administration of MK-801 increased the expression of 7 genes (NOS3, Hspb1, Hspa1a, CRH, Serpine1, Igfbp6, Snf1lk) and decreased the expression of 1 gene (Aldh1a2), which was attenuated by olanzapine. One gene (Prss12) was up-regulated after olanzapine treatment although it did not show the significant changes after MK-801 treatment. These results showed that antipsychotic drug, such as olanzapine, may alter the gene expression patterns, which were accompanied by MK-801-induced psychosis. Our results also provide us high-density DNA microarray technology could be potential approaches to find the candidate molecules for the therapeutics and also for the early diagnosis of psychiatric diseases.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.5
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• pp.2519-2525
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• 2016

There are several existing reports of microarray chip use for assessment of altered gene expression in different diseases. In fact, there have been over 1.5 million assays of this kind performed over the last twenty years, which have influenced clinical and translational research studies. The most commonly used DNA microarray platforms are Affymetrix GeneChip and Quality Control Software along with their GeneChip Probe Arrays. These chips are created using several quality controls to confirm the success of each assay, but their actual impact on gene expression profiles had not been previously analyzed until the appearance of several bioinformatics tools for this purpose. We here performed a data mining analysis, in this case specifically focused on ovarian cancer, as well as healthy ovarian tissue and ovarian cell lines, in order to confirm quality control results and associated variation in gene expression profiles. The microarray data used in our research were downloaded from ArrayExpress and Gene Expression Omnibus (GEO) and analyzed with Expression Console Software using RMA, MAS5 and Plier algorithms. The gene expression profiles were obtained using Partek Genomics Suite v6.6 and data were visualized using principal component analysis, heat map, and Venn diagrams. Microarray quality control analysis showed that roughly 40% of the microarray files were false negative, demonstrating over- and under-estimation of expressed genes. Additionally, we confirmed the results performing second analysis using independent samples. About 70% of the significant expressed genes were correlated in both analyses. These results demonstrate the importance of appropriate microarray processing to obtain a reliable gene expression profile.

• Genomics & Informatics
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• v.1 no.2
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• pp.87-93
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• 2003

DNA microarray is currently the most prominent tool for investigating large-scale gene expression data. Different algorithms for measuring gene expression levels from scanned images of microarray experiments may significantly impact the following steps of functional genomic analyses. $Affymetrix^{(R)}$ recently introduced high-density microarrays and new statistical algorithms in Microarray Suit (MAS) version 5.0$^{(R)}$. Very high correlations (0.92 - 0.97) between the new algorithms and the old algorithms (MAS 4.0) across several species and conditions were reported. We found that the column-wise array correlations had a tendency to be much higher than the row-wise gene correlations, which may be much more meaningful in the following higher-order data analyses including clustering and pattern analyses. In this paper, not only the detailed comparison of the two sets of algorithms is illustrated, but the impact of the introducing new algorithms on the further clustering analysis of microarray data and of possible pitfalls in mixing the old and the new algorithms were also described.

• Proceedings of the Korea Society of Environmental Toocicology Conference
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• 2003.10a
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• pp.173-173
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• 2003

With the introduction of DNA microarrays, a high throughput analysis of gene expression is now possible as a replacement to the traditional time-consuming Southern-blot analysis. This cDNA microarray should be ahighly favored technology in the area of molecular toxicology or analysis of environmental stresses.In this study, therefore, we developed a novel cDNA microarray for analyzing stress-specific responses in japanese Medaka fish. In the design and fabrication of this stress specific functional cDNA microarray, 123 different genes in Medaka fish were selected from eighteen different stress responsive groups and spotted on a 25${\times}$75 mm glass surface. After exposure of the fish to bisphenol A which is the one of the well-known endocrine disrupting chemicals (EDCs), over 1 or 10 days, the responses of the DNA chip were found to show distinct expression patterns according to the mode of toxic actions from environmental toxicants. As a results, they showed specific gene expression pattern to bisphenol A, additionally, the chemical spesific biomarkers could be suggested based on the chip analysis data. Therefore, this chip can be used to monitor stress responses of unknown and/or known toxic chemicals using Medaka fish and may be used for the further development of biomarkers by utilizing the gene expression patterns for known contaminants.

• Molecules and Cells
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• v.21 no.1
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• pp.82-88
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• 2006

The global pattern of growth-dependent gene expression in Streptococcus pneumoniae strains was evaluated using a high-density DNA microarray. Total RNAs obtained from an avirulent S. pneumoniae strain R6 and a virulent strain AMC96-6 were used to compare the expression patterns at seven time points (2.5, 3.5, 4.5, 5.5, 6.0, 6.5, and 8.0 h). The expression profile of strain R6 changed between log and stationary growth (the Log-Stat switch). There were clear differences between the growth-dependent gene expression profiles of the virulent and avirulent pneumococcal strains in 367 of 1,112 genes. Transcripts of genes associated with bacterial competence and capsular polysaccharide formation, as well as clpP and cbpA, were higher in the virulent strain. Our data suggest that late log or early stationary phase may be the most virulent phase of S. pneumoniae.

• 한국생물공학회:학술대회논문집
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• 2005.04a
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• pp.47-47
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• 2005

There are many different surface technologies currently applied for preparation of protein chips. However, it requires innovative surface chemistry for capture proteins to be immobilized on chip surface keeping their conformation and activity intact and their orientation right, while they bind tightly and densely in a given array spot. Proteogen has developed 'ProteoChip BP' coated with novel proprietary linker molecules $(ProLinker^{TM})$ for efficient and robust immobilizations of capture proteins by improving surface properties of molecular captures. It was demonstrated that $ProLinker^{TM}$ gave the best surface performance in preparation of protein microarray chip base plates among others currently available on the market. In particular, the $ProLinker^{TM}-based$ surface chemistry has demonstrated to provide excellent performance in preparation of 'Antibody Chip' for analysis of biomarkers as well as proteome expression profiles. The linker molecule has also shown to be well applicable for development of biosensors and micro-beads as well as protein microarray and nano-array. ProteoChip BP can be used either for preparation of high-density array by using a microarrayer or for preparation of 'Well-on-a-Chip' with low density array, which is better applicable for quantitative analysis of biomarkers or protein-protein interactions. The biomarker assay can be performed either by direct or sandwich methods of fluorescence immunoassay. Application of ProteoChip BP has been well demonstrated by the extensive studies of 1) tumor-marker assays, 2) new drug screening by using 'Integrin Chip' and 3) protein expression profile analysis. Some of experimental results will be presented.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2006.02a
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• pp.125-126
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• 2006

NimbleGen has developed strategies to use its high-density oligonucleotide microarray platform (385,000 probes per array) to map both promoter binding sites and copy number variation at very high-resolution in the human genome. Here we describe a genome-wide map of active promoters determined by experimentally locating the sites of transcription imitation complex binding throughout the human genome using microarrays combined with chromatin immunoprecipitation. This map defines 10,567 active promoters corresponding to 6,763 known genes and at least 1,196 un-annotated transcriptional units. Microarray-based comparative genomic hybridisation (CGH) is animportant research tool for investigating chromosomal aberrations frequently associated with complex diseases such as cancer, neuropsychiatric disorders, and congenital developmental disorders. NimbleGen array CGH is an ultra-high resolution (0.5-50 Kb) oligo array platform that can be used to detect amplifications and deletions and map the associated breakpoints on the whole-genome level or with custom fine-tiling arrays. For whole-genome array CGH, probes are tiled through genic and intergenic regions with a median probe spacing of 6 Kb, which provides a comprehensive, unbiased analysis of the genome.

• The Korea Genome Conference
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• 2004.07a
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• pp.46.2-46.2
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• 2004

• Asian-Australasian Journal of Animal Sciences
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• v.22 no.6
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• pp.871-884
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• 2009

Gene expression profiling is a useful tool for identifying critical genes and pathways in metabolism. The objective of this study was to determine the major differences in the expression of genes associated with metabolism and metabolic regulation in liver and mammary tissues of lactating cows. We used the Michigan State University bovine metabolism (BMET) microarray; previously, we have designed a bovine metabolism-focused microarray containing known genes of metabolic interest using publicly available genomic internet database resources. This is a high-density array of 70mer oligonucleotides representing 2,349 bovine genes. The expression of 922 genes was different at p<0.05, and 398 genes (17%) were differentially expressed by two-fold or more with 222 higher in liver and 176 higher in mammary tissue. Gene ontology categories with a high percentage of genes more highly expressed in liver than mammary tissues included carbohydrate metabolism (glycolysis, glucoenogenesis, propanoate metabolism, butanoate metabolism, electron carrier and donor activity), lipid metabolism (fatty acid oxidation, chylomicron/lipid transport, bile acid metabolism, cholesterol metabolism, steroid metabolism, ketone body formation), and amino acid/nitrogen metabolism (amino acid biosynthetic process, amino acid catabolic process, urea cycle, and glutathione metabolic process). Categories with more genes highly expressed in mammary than liver tissue included amino acid and sugar transporters and MAPK, Wnt, and JAK-STAT signaling pathways. Real-time PCR analysis showed consistent results with those of microarray analysis for all 12 genes tested. In conclusion, microarray analyses clearly identified differential gene expression profiles between hepatic and mammary tissues that are consistent with the differences in metabolism of these two tissues. This study enables understanding of the molecular basis of metabolic adaptation of the liver and mammary gland during lactation in bovine species.