• Journal of the Korean Data and Information Science Society
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• 제17권1호
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• pp.53-62
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• 2006

DNA microarray data analysis is a new technology to investigate the expression levels of thousands of genes simultaneously. Since DNA microarray data structures are various and complicative, the data are generally stored in databases for approaching to and controlling the data effectively. But we have some difficulties to analyze and control the data when the data are stored in the several database management systems or that the data are stored to the file format. The existing analysis tools for DNA microarray data have many difficult problems by complicated instructions, and dependency on data types and operating system. In this paper, we design and implement network-based analysis tool for obtaining to useful information from DNA microarray data. When we use this tool, we can analyze effectively DNA microarray data without special knowledge and education for data types and analytical methods.

• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1161-1167
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• 2006

Since microarray data structures are various and complicative, the data are generally stored in databases for approaching to and controlling the data effectively. But we have some difficulties to analyze and control the data when the data are stored in the several database management systems. The existing analysis tools for DNA microarray data have many difficult problems by complicated instructions, and dependency on data types and operating system, and high cost, etc. In this paper, we design and implement the web-based analysis tool for obtaining to useful information from DNA microarray data. When we use this tool, we can analyze effectively DNA microarray data without special knowledge and education for data types and analytical methods.

• Genomics & Informatics
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• 제5권2호
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• pp.83-87
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• 2007

The analysis of DNA microarray data is a rapidly evolving area of bioinformatics, and various types of microarray are emerging as some of the most exciting technologies for use in biological and clinical research. In recent years, microarray technology has been utilized in various applications such as the profiling of mRNAs, assessment of DNA copy number, genotyping, and detection of methylated sequences. However, the analysis of these heterogeneous microarray platform experiments does not need to be performed separately. Rather, these platforms can be co-analyzed in combination, for cross-validation. There are a number of separate laboratory information management systems (LIMS) that individually address some of the needs for each platform. However, to our knowledge there are no unified LIMS systems capable of organizing all of the information regarding multi-platform microarray experiments, while additionally integrating this information with tools to perform the analysis. In order to address these requirements, we developed a web-based LIMS system that provides an integrated framework for storing and analyzing microarray information generated by the various platforms. This system enables an easy integration of modules that transform, analyze and/or visualize multi-platform microarray data.

• 미생물학회지
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• 제39권3호
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• pp.141-147
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• 2003

여러 항진균 활성 관련 유전자들의 발현 수준을 동시에 연구하기 위하여 DNA microarray를 이용하여 유전자들의 발현 패턴을 비교 분석하였다. 본 연구에서는 항진균활성을 가지는Bacillus lentimorbus WJ5의 genomic DNA를 무작위 하게 제한효소로 절단하여 2,000개의 DNA단편을 microarray하였으며, 감마선($^{60}Co$)조사로 유도된 7종의 항진균 활성 결핍 돌연변이체와 발현양상을 정량적으로 비교하였다. Gene Cluster (Michael Risen, Stanford Uniy.)를 이용한 DNA microarray의 분석 결과, 총 408개의 DNA 단편이 발현되는 것을 확인할 수 있었으며, 이들 중 20개의 DNA단편이 항진균 활성 결핍 돌연변이체에서 발현이 억제되는 것으로 나타났다. 특히,pbuX (xanthine permease, K222), ywbA (phosphotransferase system enzyme II, K393), ptsG (PTS glucose specific enzyme II ABC component, K877), yufO (ABC transporter(ATP-binding protein), K1301), 그리고 ftsY (signal recognition particle (docking protein), K868)는 모든 돌연변이체에서 동시에 발현되는 down-regulation된 유전자들로서 물질 이동과 관련된 것으로 보고되어 있으며, 항진균 활성 관련 신호 및 물질의 이동에 관여할 것으로 사료되어진다.

• Molecular & Cellular Toxicology
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• 제1권2호
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• pp.92-98
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• 2005

DNA microarray analysis of gene expression in toxicogenomics typically requires relatively large amounts of total RNA. This limits the use of DNA microarray when the sample available is small. To confront this limitation, different methods of linear RNA amplification that generate antisense RNA (aRNA) have been optimized for microarray use. The target preparation strategy using amplified RNA in DNA microarray protocol can be divided into direct-incorporation labeling which resulted in cDNA targets (Cy-dye labeled cDNA from aRNA) and indirect-labeling which resulted in cRNA targets (i.e. Cy-dye labeled aRNA), respectively. However, despite the common use of amplified targets (cDNA or cRNA) from aRNAs, no systemic assessment for the use of amplified targets and bias in terms of hybridization performance has been reported. In this investigation, we have compared the hybridization performance of cRNA targets with cDNA targets from aRNA on a 10 K cDNA microarrays. Under optimized hybridization conditions, we found that 43% of outliers from cDNA technique and 86% from the outlier genes were reproducibly detected by both targets hybridization onto cDNA microarray. This suggests that the cRNA labeling method may have a reduced capacity for detecting the differential gene expression when compared to the cDNA target preparation. However, further validation of this discordant result should be pursued to determine which techniques possesses better accuracy in identifying truly differential genes.

• Genomics & Informatics
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• 제3권1호
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• pp.39-42
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• 2005

DNA microarray is a high-throughput biomedical technology that monitors gene expression for thousands of genes in parallel. The abundance and complexity of the gene expression data have given rise to a requirement for their systematic management and analysis to support many laboratories performing microarray research. On these demands, we developed Xperanto for integrated data management and analysis using user-friendly web-based interface. Xperanto provides an integrated environment for management and analysis by linking the computational tools and rich sources of biological annotation. With the growing needs of data sharing, it is designed to be compliant to MGED (Microarray Gene Expression Data) standards for microarray data annotation and exchange. Xperanto enables a fast and efficient management of vast amounts of data, and serves as a communication channel among multiple researchers within an emerging interdisciplinary field.

• 한국미생물·생명공학회지
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• 제38권1호
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• pp.70-76
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• 2010

The single-stranded large circular (LC)-sense DNA were utilized as probes for DNA chip experiments. The microarray experiment using LC-sense DNA probes found differentially expressed genes in A549 cells as compared to WI38VA13 cells, and microarray data were well-correlated with data acquired from quantitative real-time RT-PCR. A 5K LC-sense DNA microarray was prepared, and the repeated experiments and dye swap test showed consistent expression patterns. Subsequent functional analysis using LC-antisense library of overexpressed genes identified several genes involved in A549 cell growth. These experiments demonstrated proper feature of LC-sense molecules as probe DNA for microarray and the potential utility of the combination of LC-sense microarray and antisense libraries for an effective functional validation of genes.

• 한국독성학회:학술대회논문집
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• 한국독성학회 2000년도 국제심포지움 및 추계학술대회
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• pp.31-41
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• 2000

The major issue in the post genome sequencing era is determination of gene expression patterns in variety of biological systems. A microarray system is a powerful technology for analyzing the expression profile of thousands of genes at one experiment. In this study, we constructed cDNA microarray which carries 2,304 cDNAS derived from oligo-capped mouse cDNA library. Using this hand-made microarray we determined gene expression in various biological systems. To determine tissue specific genes, we compared Nine genes were highly-expressed in adult mouse brain compared to kidney, liver, and skeletal muscle. Tissue distribution analysis using DNA microarray extracted 9 genes that were predominantly expressed in the brain. A database search showed that five of the 9 genes, MBP, SC1, HiAT3, S100 protein-beta, and SNAP25, were previously known to be expressed at high level in the brain and in the nervous system. One gene was highly sequence similar to rat S-Rex-s/human NSP-C, suggesting that the gene is a mouse homologue. The remaining three genes did not match to known genes in the GenBank/EMBL database, indicating that these are novel genes highly-expressed in the brain. Our DNA microarray was also used to detect differentiation specific genes, hormone dependent genes, and transcription-factor-induced genes. We conclude that DNA microarray is an excellent tool for identifying differentially expressed genes.

• 한국정보과학회논문지:시스템및이론
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• 제30권10호
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• pp.544-555
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• 2003

DNA 마이크로어레이 실험으로 나오는 데이타는 아주 많은 양의 유전자 발현 정보를 담고 있기 때문에 적절한 분석 방법이 필요하다. 대표적인 분석 방법은 계층적 클러스터링(hierarchical clustering) 방법이다. 본 논문에서는 계층적 클러스터링의 결과로 나오게 되는 덴드로그램(dendrogram)에 대해서 후처리(post-Processing)를 시행함으로써 DNA 마이크로어레이 데이타 분석을 더 용이하게 해주는 리프오더링(leaf-ordering)에 대해서 연구하였다. 먼저, 기존의 리프오더링 알고리즘들을 분석하였고, 리프오더링 알고리즘의 새로운 접근 방식을 제안하였다. 또한 이에 대한 성능을 실험하고 분석하기 위해서 계층적 클러스터링과 몇 가지 리프오더링 알고리즘들, 그리고 제안된 접근 방식을 직접 구현한 HCLO (Hierarchical Clustering & Leaf-Ordering Tool)에 대해서 소개하였다.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2006년도 Principles and Practice of Microarray for Biomedical Researchers
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• pp.98-107
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• 2006

Chromosomal copy number changes (aneuploidies) are common in human populations. The extra chromosome can affect gene expression by whole-genome level. By gene expression microarray analysis, we want to find aberrant gene expression due to aneuploidies in Klinefelter (+X) and Down syndrome (+21). We have analyzed the inactivation status of X-linked genes in Klinefelter Syndrome (KS) by using X-linked cDNA microarray and cSNP analysis. We analyzed the expression of 190 X-linked genes by cDNA microarray from the lymphocytes of five KS patients and five females (XX) with normal males (XY) controls. cDNA microarray experiments and cSNP analysis showed the differentially expressed genes were similar between KS and XX cases. To analyze the differential gene expressions in Down Syndrome (DS), Amniotic Fluid (AF)cells were collected from 12 pregnancies at $16{\sim}18$ weeks of gestation in DS (n=6) and normal (n=6) subjects. We also analysis AF cells for a DNA microarray system and compared the chip data with two dimensional protein gel analysis of amniotic fluid. Our data may provide the basis for a more systematic identification of biological markers of fetal DS, thus leading to an improved understanding of pathogenesis for fetal DS.