• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.366-370
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• 2005

Tissue microarry is one of the high throughput technologies in the post-genomic era. Using tissue microarray, the researchers are able to investigate large amount of gene expressions at the level of DNA, RNA, and protein The important aspect of tissue microarry is its ability to assess a lot of biomarkers which have been used in clinical practice. To manipulate the categorical data of tissue microarray, we applied Bayesian network classifier algorithm. We identified that Bayesian network classifier algorithm could analyze tissue microarray data and integrating prior knowledge about gastric cancer could achieve better performance result. The results showed that relevant integration of prior knowledge promote the prediction accuracy of survival status of the immunohistochemical tissue microarray data of 18 tumor suppressor genes. In conclusion, the application of Bayesian network classifier seemed appropriate for the analysis of the tissue microarray data with clinical information.

• 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.

• KOGO NEWS
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• v.5 no.4
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• pp.17-25
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• 2005

• Environmental Analysis Health and Toxicology
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• v.20 no.4 s.51
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• pp.327-332
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• 2005

장기간 노출 시 발암 등 인체 유해성을 갖는 환경유래 내분비장애물질(endocrine disrupting chemicals, EDCs)에 대한 선택적이고 민감한 노출지표를 개발하기 위하여 본 연구에서는 DNA microarray를 이용하였다. 피험자는 아직 특별한 질환을 갖지 않는 18세 이상 연령, 성을 맞춘 EDCs고농도 노출군(N = 16)과 저농도군(N = 16)으로 구성되었다. 노출정도 구분은 10년 이상 거주지가 K산업폐기물 소각장과 2.5 km 반경 내, 외 인지에 따라 고노출군,저노출군으로 구분하였다. 피험자의 말초혈에서 total RNA를 분리, 각 군당 B인씩 pool로 cDNA를 합성하여 oligonucleotide DNA 칩에 적용하였다. 유전자발현의 차이를 GenePixPro 4.0 software를 이용하여 분석하였다. 총 3장의 칩을 이용하여 공통적으로 저노출군보다 고노출군에서 2배 이상 발현의 증가를 보인 유전자는 plasminogen activator(PLAT)등 12종이 관찰되었고, l/2이하로 발현의 감소를 보인 유전자는 kallikrein 3 (KLK3)등 29종이었다. 이 들 유전자는 PLAT등 면역계 반응에 관여하는 유전자 및 apoptosis, transport, G protein, chromatin, 암화, 발생 (development), 대사 등에 관여하는 유전자들이었다. 그러므로 KLK3등 본 연구에서 발굴한 유전자는 향후 확대된 인구에서 본 연구 결과의 확인을 통하여 EDCs특이적 노출지표로써, 나아가 암 등 EDCs관련 질병의 기전 및 병인학을 구명하는데 이용가치가 높다고 사료된다.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1005-1021
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• 2007

Traditional procedures for DNA microarray data analysis are to preprocess and normalize the gene expression data, and then to analyze the normalized data using statistical tests. Drawbacks of the traditional methods are: genuine biological signal may be unwillingly eliminated together with artifacts, the limited number of arrays per gene make statistical tests difficult to use the normality assumption or nonparametric method, and genes are tested independently without consideration of interrelationships among genes. A novel method using average rank in each array is proposed to eliminate such drawbacks. This average rank method monitors differentially regulated genes among genetically different groups and the selected genes are somewhat different from those selected by traditional P-value method. Addition of genes selected by the average rank method to the traditional method will provide better understanding of genetic differences of groups.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.733-735
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• 2003

DNA Microarray 기술은 유전자의 발현여부를 매우 빠르게 검사할 수 있는 도구이며 각종 질병의 발생여부를 예측하기 위한 정보를 제공한다. 유전자 발현 데이터로부터 암의 발생 여부를 예측하기 위해서는 기존의 접근방법과 다른 기계학습 기법이 요구된다. 일반적으로 샘플의 개수가 극히 적은 반면에 특징의 개수는 수천에서 수만 개가 존재하기 때문에 문제의 특성에 맞는 분류기의 구조를 결정하는 것이 매우 어려운 일이기 때문이다. 진화 신경망은 신경망의 구조와 가중치를 동시에 학습하며 사용자는 각 개체의 적합도를 평가할 수 있는 방법만 제공해 주면된다. 특히 신경망의 구조를 사전에 고정하지 않아도 되는 장점이 있기 때문에 전문적인 지식이 없는 사용자라도 이용가능하다. 대장암 데이터에 대한 실험결과 제안하는 분류기 모델이 다층 퍼셉트론, SVM (support vector machine), 최근접 이웃 방법에 비해 향상된 성능을 보였다.

• Journal of Computing Science and Engineering
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• v.4 no.4
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• pp.350-367
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• 2010

Microarray technology is an interdisciplinary technique that promises a revolutionary progress toward better health and improved quality of life. The paper focuses on the development of an efficient software package, equipped with already well-known methods; also some new methods are proposed that will allow the processing and analysis of thousands of genes on microarray images. The microarray analysis software package (called SmartArray), newly proposed in this paper verifies, through microarray analysis, dramatic changes in the mRNA, protein, and activity level in the rat retina during light deprivation, which have been demonstrated in previous biological experiments. The analysis results demonstrate that SmartArray can successfully find many changes in gene expression levels in each subarray and classify them according to their significance.

• KSBB Journal
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• v.24 no.3
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• pp.259-266
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• 2009

AfsR2 in Streptomyces lividans, a 63-amino acid protein with limited sequence homology to Streptomyces sigma factors, has been known for a global regulatory protein stimulating multiple antibiotic biosynthetic pathways. Although the detailed regulatory mechanism of AfsK-AfsR-AfsR2 system has been well characterized, very little information about the AfsR2-dependent down-stream regulatory genes were characterized. Recently, the null mutant of afsS in S. coelicolor (the identical ortholog of afsR2) has been characterized through DNA microarray system, revealing that afsS deletion regulated several genes involved in antibiotic biosynthesis as well as phosphate-starvation. Through comparative DNA microarray analysis of afsR2-overexpressed S. lividans, here we also identify several afsR2-dependent genes involved in phosphate starvation, morphological differentiation, and antibiotic regulation in S. lividans, confirming that the AfsR2 plays an important pleiotrophic regulatory role in Streptomyces species.

• Microbiology and Biotechnology Letters
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• v.44 no.4
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• pp.563-570
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• 2016

Two Streptomyces griseus strains, a wild-type strain and an A-factor-dependent transcriptional activator mutant strain harboring multiple copies of a gene, dasA, that encodes a substrate-binding protein of the ATP-binding cassette transporter, showed severe ectopic sporulation of young substrate hyphae in response to glucose. The effect of dasA overexpression on the ectopic sporulation of Streptomyces strains was evaluated by comparing the transcriptomes of the strain harboring multiple copies of dasA and a strain harboring empty vector. By DNA microarray, 4 genes (SGR794, SGR2469, SGR3656, and SGR3657) and 3 clusters (SGR795-797, SGR2377-2378, and SGR6997-6998) were differentially expressed by more than 2-fold in S. griseus strains harboring dasA. The DNA microarray result was validated by low-resolution S1 nuclease mapping.

• The Korean Journal of Nuclear Medicine
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• v.37 no.1
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• pp.43-52
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• 2003

Microarray technology allows the simultaneous analysis of gene expression patterns of thousands of genes, in a systematic fashion, under a similar set of experimental conditions, thus making the data highly comparable. In some cases arrays are used simply as a primary screen loading to downstream molecular characterization of individual gene candidates. In other cases, the goal of expression profiling is to begin to identify complex regulatory networks underlying developmental processes and disease states. Microarrays were originally used with ceil lines or other simple model systems. More recently, microarrays have been used in the analysis of more complex biological tissues including neural systems and the brain. The application of cDNA arrays in neuropsychiatry has lagged behind other fields for a number of reasons. These include a requirement for a large amount of input probe RNA In fluorescent-glass based array systems and the cellular complexity introduced by multicellular brain and neural tissues. An additional factor that impacts the general use of microarrays in neuropsychiatry is the lack of availability of sequenced clone sets from model systems. While human cDNA clones have been widely available, high qualify rat, mouse, and drosophilae, among others are just becoming widely available. A final factor in the application of cDNA microarrays in neuropsychiatry is cost of commercial arrays. As academic microarray facilitates become more commonplace custom made arrays will become more widely available at a lower cost allowing more widespread applications. in summary, microarray technology is rapidly having an impact on many areas of biomedical research. Radioisotope-nylon based microarrays offer alternatives that may in some cases be more sensitive, flexible, inexpensive, and universal as compared to other array formats, such as fluorescent-glass arrays. In some situations of limited RNA or exotic species, radioactive membrane microarrays may be the most practical experimental approach in studying psychiatric and neurodegenerative disorders, and other complex questions in the brain.