• Journal of KIISE:Computer Systems and Theory
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• v.29 no.7
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• pp.411-421
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• 2002

In this Paper we propose a new Image analysis algorithm for microarray processing and a method to locate the position of the grid cell using the topology of the grid spots. Microarray is a device which enables a parallel experiment of 10 to 100 thousands of test genes in order to measure the gene expression. Because of the huge data obtained by a experiment automated image analysis is needed. The final output of this microarray experiment is a set of 16-bit gray level image files which consist of grid-structured spots. In this paper we propose one algorithm which located the address of spots (spot indices) using graph structure from image data and a method which determines the precise location and shape of each spot by measuring the inclination of grid structure. Several experiments are given from real data sets.

• Proceedings of the Korean Society of Life Science Conference
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• 2000.06a
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• pp.3-8
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• 2000

The complete genome sequence of a Gram-positive bacterium .Bacillus subtilis has recently been reported and it is now clear that more than 50% of its ORFs have no known function (1). To study the global gene expression in B. subtilis at single gene resolution, we have tested the glass DNA microarrays in a step-wise fashion. As a preliminary experiment, we have created arrays of PCR products for 14 ORF whose transcription patterns have been well established through transcriptional mapping analysis. We measured changes in mRNA transcript levels between early exponential and stationary phase by hybridizing fluorescently labeled cDNA (with Cy3-UTP and Cy5-UTP) onto the array. We then compared the microarray data to confirm that the transcription patterns of these genes are well consistent with the known Northern analysis data. Since the preliminary test has been successful, we scaled up the experiments to ${\sim}$94% of the 4,100 annotated ORFs for the complete genome sequence of B. subtilis. Using this whole genomic microarray, we searched genes that are catabolite-repressive and those that are under the control of ${\sigma}^{Y}$, one of the functionally unknown ECF sigma factors. From these results, we here report that we have established DNA microarray techniques that are applicable for the whole genome of B. subtilis.

• 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.

• Korean Journal of Ichthyology
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• v.18 no.2
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• pp.65-77
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• 2006

Gene transcripts potentially responsive to the heat stress were surveyed by cDNA microarray analysis in mud loach (Misgurnus mizolepis). Transcriptional profiles of hepatic tissue in the fish exposed to either $23^{\circ}C$ or $32^{\circ}C$ for 4 weeks were compared each other by 3 replicated hybridization assays using 1,124 unigene clones selected from mud loach liver expressed sequence tags (ESTs). A total of 93 clones showed the substantially increased mRNA levels (>2-fold) in $32^{\circ}C$-exposed group when compared in $23^{\circ}C$control group. It includes various enzymes and proteins involved in energy pathway, protease/protein metabolisms, immune/antioxidant functions, cytoskeleton/cell structure, transport and/or signal transduction. Maximum level of increase was up to 15-fold relative to $23^{\circ}C$ treatment. Heat exposure also resulted in the significant decrease (less than 50% relative to $23^{\circ}C$-exposed fish) of the transcriptional activities in 85 genes. Besides the above categories, yolk protein (vitellogenin) and ribosomal proteins were notably down regulated in the fish exposed to heat stress. A number of novel gene transcripts were also detected in both up-regulated and down-regulated groups.

• 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.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.17-23
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• 2005

In this paper we consider the well-known semiparametric proportional hazards models for survival analysis. These models are usually used with few covariates and many observations (subjects). But, for a typical setting of gene expression data from DNA microarray, we need to consider the case where the number of covariates p exceeds the number of samples n. For a given vector of response values which are times to event (death or censored times) and p gene expressions(covariates), we address the issue of how to reduce the dimension by selecting the significant genes. This approach enables us to estimate the survival curve when n ${\ll}$p. In our approach, rather than fixing the number of selected genes, we will assign a prior distribution to this number. The approach creates additional flexibility by allowing the imposition of constraints, such as bounding the dimension via a prior, which in effect works as a penalty To implement our methodology, we use a Markov Chain Monte Carlo (MCMC) method. We demonstrate the use of the methodology to diffuse large B-cell lymphoma (DLBCL) complementary DNA (cDNA) data and Breast Carcinomas data.

• Biomedical Science Letters
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• v.15 no.3
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• pp.261-263
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• 2009

Methylprednisolone is a synthetic glucocorticoid which is usually taken intravenously for many neurosurgical diseases which cause edema including brain tumor, and trauma including spinal cord injury. Methylprednisolone reduces swelling and decreases the body's immune response. It is also used to treat many immune and allergic disorders, such as arthritis, lupus, psoriasis, asthma, ulcerative colitis, and Crohn's disease. To identify genes expressed during methylprednisolone treatment against neurons of rats (PC12 cells), DNA microarray method was used. We have isolated 2 gene groups (up- or down-regulated genes) which are methylprednisolone differentially expressed in neurons. Lipocalin 3 is the gene most significantly increased among 772 up-regulated genes (more than 2 fold over-expression) and Aristaless 3 is the gene most dramatically decreased among 959 down-regulated genes (more than 2 fold down-expression). The gene increased expression of Fgb, Thbd, Cfi, F3, Kngl, Serpinel, C3, Tnfrsf4 and Il8rb are involved stress-response gene, and Nfkbia, Casp7, Pik3rl, I11b, Unc5a, Tgfb2, Kitl and Fgf15 are strongly associated with development. Cell cycle associated genes (Mcm6, Ccnb2, Plk1, Ccnd1, E2f1, Cdc2a, Tgfa, Dusp6, Id3) and cell proliferation associated genes (Ccl2, Tnfsf13, Csf2, Kit, Pim1, Nr3c1, Chrm4, Fosl1, Spp1) are down-regulated more than 2 times by methylprednisolone treatment. Among the genes described above, 4 up-regulated genes are confirmed those expression by RT-PCR. We found that methylprednisolone is related to expression of many genes associated with stress response, development, cell cycle, and cell proliferation by DNA microarray analysis. However, We think further experimental molecular studies will be needed to figure out the exact biological function of various genes described above and the physiological change of neuronal cells by methylprednisolone. The resulting data will give the one of the good clues for understanding of methylprednisolone under molecular level in the neurons.

• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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• pp.175-181
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• 2002

cDNA microarray experiments permit us to investigate the expression levels of thousands of genes simultaneously and to make it easy to compare gene expression from different populations. However, researchers are asked to be cautious in interpreting the results because of the unexpected sources of variation such as systematic errors from the microarrayer and the difference of cDNA dye intensity. And the scanner itself calculates both of mean and median of the signal and background pixels, so it follows a selection which raw data will be used in analysis. In this paper, we compare the results in each case of using mean and median from the raw data and normalization methods in reducing the systematic errors with arm's skin cells of old and young males. Using median is preferable to mean because the distribution of the test statistic (t-statistic) from the median is more close to normal distribution than that from mean. Scaled print tip normalization is better than global or lowess normalization due to the distribution of the test-statistic.