• Proceedings of the Korean Society of Toxicology Conference
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• 2002.05a
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• pp.81-81
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• 2002

The recent development of cDNA microarray or cDNA chip technology has made it possible to analyze the expression of thousands of genes at once. In present study, we made radioresistant clones (#1 and #4) from NIH3T3 cells which are not tumorigenic and we identified 4 genes using microarray system, cdk6, cdc25B, mdm-2 and nidogene, which were altered in radiaiton resistanct NIH3T3 cells.(omitted)

• Molecules and Cells
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• v.22 no.3
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• pp.254-261
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• 2006

DNA microarray is a powerful tool for high-throughput analysis of biological systems. Various computational tools have been created to facilitate the analysis of the large volume of data produced in DNA microarray experiments. Normalization is a critical step for obtaining data that are reliable and usable for subsequent analysis such as identification of differentially expressed genes and clustering. A variety of normalization methods have been proposed over the past few years, but no methods are still perfect. Various assumptions are often taken in the process of normalization. Therefore, the knowledge of underlying assumption and principle of normalization would be helpful for the correct analysis of microarray data. We present a review of normalization techniques from single-labeled platforms such as the Affymetrix GeneChip array to dual-labeled platforms like spotted array focusing on their principles and assumptions.

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2003.10a
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• pp.81.1-81
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• 2003

Although plants have evolved to possess various defense mechanisms from local biotic and abiotic stressors, most of yield loss is caused by theses stressors. Recent studies have revealed that several different stress responsive reactions are inter-networking. Therefore, the identification and dissection of stress responsive genes is an essential and first step towards understanding of the global defense mechanism in response to various stressors. For this purpose, we applied cDNA microarray analysis, because it has powerful ability to monitor the global gene expression in a specific situation. To date, more than 10,000 non-redundant genes were identified from seven different cDNA libraries and deposited in our EST database (http://plant.pdrs.re.kr/ks200201/pepper.html). For this study, we have built 5K cDNA microarray containing 4,685 unigene clones from three different cDNA libraries. Monitoring of gene expression profiles of hot pepper interactions with biotic stress, abiotic stresses and chemical treatments will be presented. Although this work shows expression profiling at the sub-genomic level, this could be a good starting point to understand the complexity of global defense mechanism in hot pepper.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.59-60
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• 2000

The past few years have seen a dramatic increase in gene expression data on the basis of DNA microarrays or DNA chips. Going beyond a generic view on the genome, microarray data are able to distinguish between gene populations in different tissues of the same organism and in different states of cells belonging to the same tissue. This affords a cell-wide view of the metabolic and regulatory processes under different conditions, building an effective basis for new diagnoses and therapies of diseases. In this talk we present machine learning techniques for effective mining of DNA microarray data. A brief introduction to the research field of machine learning from the computer science and artificial intelligence point of view is followed by a review of recently-developed learning algorithms applied to the analysis of DNA chip gene expression data. Emphasis is put on graphical models, such as Bayesian networks, latent variable models, and generative topographic mapping. Finally, we report on our own results of applying these learning methods to two important problems: the identification of cell cycle-regulated genes and the discovery of cancer classes by gene expression monitoring. The data sets are provided by the competition CAMDA-2000, the Critical Assessment of Techniques for Microarray Data Mining.

• Biotechnology and Bioprocess Engineering:BBE
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• v.9 no.2
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• pp.93-99
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• 2004

Pathogens pose a significant threat to humans, animals, and plants. Consequently, a considerable effort has been devoted to developing rapid, convenient, and accurate assays for the detection of these unfavorable organisms. Recently, DNA-microarray based technology is receiving much attention as a powerful tool for pathogen detection. After the target gene is first selected for the unique identification of microorganisms, species-specific probes are designed through bioinformatic analysis of the sequences, which uses the info rmation present in the databases. DNA samples, which were obtained from reference and/or clinical isolates, are properly processed and hybridized with species-specific probes that are immobilized on the surface of the microarray for fluorescent detection. In this study, we review the methods and strategies for the development of DNA microarray for pathogen detection, with the focus on probe design.

• Journal of Periodontal and Implant Science
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• v.38 no.sup2
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• pp.299-308
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• 2008

Purpose: The aim of this study was to evaluate adhesion and gene expression of the MC3T3-E1 cells cultured on machined titanium surface (MS) and anodized titanium surface (AS) using MTT test, Scanning electron micrograph and cDNA microarray. Materials and Methods: The MTT test assay was used for examining the proliferation of MC3T3-E1 cells, osteoblast like cells from Rat calvaria, on MS and AS for 24 hours and 48 hours. Cell cultures were incubated for 24 hours to evaluate the influence of the substrate geometry on both surfaces using a Scanning Electron Micrograph (SEM). The cDNA microarray Agilent Rat 22K chip was used to monitor expressions of genes. Results: After 24 hours of adhesion, the cell density on AS was higher than MS (p < 0.05). After 48 hours the cell density on both titanium surfaces were similar (p > 0.05). AS had the irregular, rough and porous surface texture. After 48 hours incubation of the MC3T3-E1 cells, connective tissue growth factor (CTGF) was up-regulated on AS than MS (more than 2 fold) and the insulin-like growth factor 1 receptor was down-regulated (more than 2 fold) on AS than MS. Conclusion: Microarray assay at 48 hours after culturing the cells on both surfaces revealed that osteoinductive molecules appeared more prominent on AS, whereas the adhesion molecules on the biomaterial were higher on MS than AS, which will affect the phenotype of the plated cells depending on the surface morphology.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.05a
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• pp.198-201
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• 2005

DNA microarray 칩은 신약 개발, 유전적 질환 진단, Bio-molecular 상호작용 연구, 유전자의 기능연구 등 폭넓게 사용되고 있다. 이 논문은 cDNA mimcroarray 데이터를 분석하기 위한 웹형태의 시스템 개발에 대한 내용을 다룬다. 하나의 cDNA microarray에는 수 백에서 수 만개의 유전자가 심어져 있으며, 데이터를 분석할 때 대량의 데이터와 다양한 형태의 오류로 인해서 데이터간의 차이를 보정하는 분석 도구와 통계적 기법들이 사용되어야 한다. 본 논문에서는 가상 칩 뷰어를 이용하여 실제 microarray 데이터의 foreground intensity에서 백그라운드의 intensity를 제거하여 일반화된 칩 이미지를 생성한다. 이 가상 칩 뷰어는 여러 가지 필터효과와 서로 다른 두 형광의 차이를 조정하는 global normalization 기법을 사용하여 발현 유전자 분석을 시각적으로 할 수 있고, 중복된 마이크로어레이 칩 데이터를 통하여 시간이 많이 걸리는 분석전 칩의 유효성을 검토할 수 있다. 칩 데이터의 normalization을 위한 통계 방법으로 R 통계 도구와 linear 모델을 사용하여 microarray 칩의 유전자 발현 양상을 분석한다. 통계적 방법을 사용하지 않은 데이터를 추출, 이 데이터의 패턴 그래프 그리고 발현 레벨을 분류하여 마이크로어레이의 각 스팟의 유효성 검토의 정확성을 높였다. 이 시스템은 칩의 유효성 검토, 스팟의 유효성 검토, 유전자 선정에 대해 분석의 용이성과 정확성을 높일 수 있었다.

• Korean Journal of Environmental Biology
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• v.22 no.3
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• pp.472-477
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• 2004

To study the radiation related gene expression in mutants of Bacillus lentimorbus WJ5 induced by gamm radiation, the simultaneous gene expression was analyzed by DNA micro array. We constructed DNA chips including two thousand randomly digested genome spots of B. lentimorbus WJ5 and compared its quantitative aspect with seven mutants induced by gamma radiation $(^{60}/Co)$. From the cluster analysis of gene expression pattern, totally 408 genes were expressed and 27 genes were significantly upregulated by the gamma radiation in all mutants. Especially, genes involved in repair (mutL, mutM), energy metabolism (acsA, sdhB, pgk, yhjB, citB), protease (npr), and reduction response to oxidative stress (HMM) were simultaneously upregulated. It seems that the induction of the direct and/or indirect repair related genes in mutants induced by gamma radiation could be remarkably different from the adaptive responses against acute exposure to radiation.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.167-172
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• 2007

Long gene sequences and their products have been studied by many methods. The use of DNA(Deoxyribonucleic acid) microarray technology has resulted in an enormous amount of data, which has been difficult to analyze using typical research methods. This paper proposes that mass data be analyzed using division clustering with the K-means clustering algorithm. To demonstrate the superiority of the proposed method, it was used to analyze the microarray data from rice DNA. The results were compared to those of the existing K-meansmethod establishing that the proposed method is more useful in spite of the effective reduction of performance time.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.471-472
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• 2007