• 한국환경성돌연변이발암원학회지
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• 제22권4호
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• pp.274-278
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• 2002

Phthalates, suspected endocrine disruptor, are plasticizer and solvent used in industry, and some phthalates are known as potential carcinogen. Most common human exposure to this compounds may occur with contaminated food. It may migrate into food from plastic wrap or may enter food from general environmental contamination, and it has become widespread environmental pollutants, thus leading to a variety of phthalates that possibly threaten the public health. Dibutyl phthalate (DBP) may playa part of cell proliferator, which mediates changes in gene expression and the metabolism of xenobiotics. An understanding of the role of DBP in modulating gene regulation should provide insight regarding mechanisms of DBP induced xenoestrogenic impact. To elucidate the type of genes that are associated with estrogenic activity induced by DBP at the dose (10$^{-8}$ M) appeared proliferating effects, the pattern of gene expression in MCF7 cells was compared between 17$\beta$-estradiol and DBP exposure in the cDNA microarray. From the results, it showed some differences of gene expression patterns between MCF7 cells treated with 17$\beta$-estradiol and DBP, and also DBP shows estrogenic potential with changes in estrogen-related gene expression levels.

• Genomics & Informatics
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• 제3권1호
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• pp.30-34
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• 2005

Microarray technology makes it possible to measure the expressions of tens of thousands of genes simultaneously under various experimental conditions. Identifying differentially expressed genes in each single experimental condition is one of the most common first steps in microarray gene expression data analysis. Reasonable choices of thresholds for determining differentially expressed genes are used for the next-stap-analysis with suitable statistical significances. We present a supervised model for identifying DEGs using pathway information based on the global connectivity structure. Pathway information can be regarded as a collection of biological knowledge, thus we are trying to determine the optimal threshold so that the consequential connectivity structure can be the most compatible with the existing pathway information. The significant feature of our model is that it uses established knowledge as a reference to determine the direction of analyzing microarray dataset. In the most of previous work, only intrinsic information in the miroarray is used for the identifying DEGs. We hope that our proposed method could contribute to construct biologically meaningful structure from microarray datasets.

• Genomics & Informatics
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• 제1권2호
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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.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2001년도 제2회 생물정보 워크샵 (DNA Chip Bioinformatics)
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• pp.97-115
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• 2001

cDNA microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. Many statistical analysis tools become widely applicable to the analysis of cDNA microarray data. In this talk, we consider a two-way ANOVA model to differentiate genes that have high variability and ones that do not. Using this model, we detect genes that have different gene expression profiles among experimental groups. The two-way ANOVA model is illustrated using cDNA microarrays of 3,800 genes obtained in an experiment to search for changes in gene expression profiles during neuronal differentiation of cortical stem cells.

• The Korean Journal of Physiology and Pharmacology
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• 제10권4호
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• pp.173-180
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• 2006

Microglial activation is thought to play a role in the pathogenesis of many brain disorders. Therefore, understanding the response of microglia to noxious stimuli may provide insights into their role in disorders such as stroke and neurodegeneration. Many genes involved in this response have been identified individually, but not systematically. In this regards, the microarray system permitted to screen a large number of genes in biological or pathological processes. Therefore, we used microarray technology to evaluate the effect of oxygen glucose deprivation (OGD) and reperfusion on gene expression in microglia under ischemia-like and activating conditions. Primary microglial cultures were prepared from postnatal mice brain. The cells were exposed to 4 hrs of OGD and 1 h of reperfusion at $37^{\circ}C$. Isolated mRNA were run on GeneChips. After OGD and reperfusion, ＞2-fold increases of 90 genes and ＞2-fold decrease of 41 genes were found. Among the genes differentially increased by OGD and reperfusion in microglia were inflammatory and immune related genes such as prostaglandin E synthase, $IL-1{\beta}$, and $TNF-{\alpha}$. Microarray analysis of gene expression may be useful for elucidating novel molecular mediators of microglial reaction to reperfusion injury and provide insights into the molecular basis of brain disorders.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2006년도 Principles and Practice of Microarray for Biomedical Researchers
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• pp.78-78
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• 2006

Gene expression analysis can be performed by one-color (intensity-based) or two-color (ratio-based) microarray platforms depending on the specific applications and needs of the researcher. The traditional two-color approach is well founded from a historical and scientific standpoint, and the one-color approach, when paired with high quality microarrays and a robust workflow, offers additional flexibility in experimental design. Two of the major requirements of any microarray platform are system reproducibility, which provides the means for high confidence experiments and accurate comparison across multiple samples; and high sensitivity, for the detection of significant gene expression changes, including small fold changes across multiple gene sets. Each of these requirements is fulfilled by the Agilent One-color Gene Expression Platform as illustrated by the data included in this study. As a result, researchers have the ability to take advantage of the enhanced performance and sensitivity of Agilent's 60-mer oligonucleotide microarrays, and experience the first commercial microarray platform compatible with both one- and two-color detection.

• Molecules and Cells
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• 제25권2호
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• pp.279-288
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• 2008

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

• Molecular & Cellular Toxicology
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• 제2권1호
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• pp.35-47
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• 2006

2, 3, 7, 8-Tetrachlorodibenzo-p-dioxin (TCDD) are well known as the most toxic environmental compound in these days. Many researches are reported that dioxin produces multiple toxic effects, such as endocrine toxicity, reproductive toxicity, immunotoxicity and cancer. In this study, we carried to discover novel evidence for previously unknown gene expression patterns in human exposed to dioxin by using radioactive cDNA microarray. 548 workers who were divided into experimental and control groups according to their urinary Naphthol levels were enrolled in our study. Blood mRNA in human was isolated, and the gene expression profiles were analyzed by cDNA microarray. Gene expression analysis identified 52 genes which exhibited a significant change. In our study, most notably, genes involved in cell cycle, cell proliferation, signal transduction and apoptosis in human exposed to dioxin, such as CCND3, TSHR, and EFRN5, were up-regulated. In the current study, we observed gene expression of people that are exposed to dioxin using radioactive cDNA microarray. Through these results, we suggest when objects are exposed to toxic compounds, such as dioxin, the radioactive cDNA microarray may be using in sensitively detecting of cancerous change.

• Reproductive and Developmental Biology
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• 제37권1호
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• pp.17-22
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• 2013

Although assisted reproductive technology is very useful to develop novel and therapeutic biomaterials for reproduction, research on molecular mechanism of folliculogenesis in pig is not clear. Therefore, the alteration of gene expression during follicular development in pigs was examined in this study. The expression of folliculogenesis-related genes was quantified in preantral ($250{\sim}300{\mu}m$) and antral (> $300{\mu}m$ in diameter) follicles, and overall gene expression was evaluated by a genome-wide microarray. The microarray results showed that 219 genes were differentially expressed, and of those, 10 and 22 known genes showed higher and less expression at the preantral stage than at antral stages, respectively. Among them, the expression of NR0B1, PPARG, GATA4, and ANXA2 genes related to folliculogenesis was validated by quantitative real-time PCR analysis. The expression of PPARG and GATA4 genes were increased at antral stages, but a significantly stage-specific increase (p<0.05) was only detected in annexin A2 (ANXA2) in antral-stage follicles. The expression of NR0B1 genes was increased at preantral stage and these patterns of gene expression were comparable to the results obtained by microarray analysis. We propose that the systematical regulation of genes supporting specific follicle stage should be employed for improved in-vitro folliculognesis.

• Molecular & Cellular Toxicology
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• 제3권4호
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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.