• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.183-187
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• 2005

In this paper, we propose a heuristic method to select features using a Two-Phase Markov Blanket-based (TPMB) algorithm. The first phase, filtering phase, of TPMB algorithm works by filtering the obviously redundant features. A non-linear correlation method based on Information theory is used as a metric to measure the redundancy of a feature [1]. In second phase, approximating phase, the Markov Blanket (MB) of a system is estimated by employing the concept of cross entropy to identify the MB. We perform experiments on microarray data and report two popular dataset, AML-ALL [3] and colon tumor [4], in this paper. The experimental results show that the TPMB algorithm can significantly reduce the number of features while maintaining the accuracy of the classifiers.

• Genomics & Informatics
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• v.13 no.2
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• pp.40-44
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• 2015

DNA microarray and next-generation sequencing provide data that can be used for the genetic analysis of multiple quantitative traits such as gene expression levels, transcription factor binding profiles, and epigenetic signatures. In particular, chromatin opening is tightly coupled with gene transcription. To understand how these two processes are genetically regulated and associated with each other, we examined the changes of chromatin accessibility and gene expression in response to genetic variation by means of quantitative trait loci mapping. Regulatory patterns commonly observed in yeast and human across different technical platforms and experimental designs suggest a higher genetic complexity of transcription regulation in contrast to a more robust genetic architecture of chromatin regulation.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10a
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• pp.6-10
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• 2006

마이크로어레이 실험의 등장으로 한 번에 수백 개에서 수천 개의 유전자를 실험할 수 있게 되었다. 이는 기존의 실험과 비교했을 때 질적인 측면과 양적인 측면에서 가히 혁신적이라 할 수 있다. 마이크로어레이 칩을 이용한 실험에서 쏟아져 나오는 엄청난 데이터를 비교, 분석, 관리하기 위해서는 실험실의 마이크로어레이 분석 소프트웨어나 시스템간의 데이터 형식이 호환되어야 하며, 소프트웨어의 지원 또한 획기적이고 효율적이어야 한다. 본 논문에서는 다양한 종류의 마이크로어레이 입력 데이터 및 분석 데이터를 다룰 수 있고, 표준 파일 형식으로의 변환 기능을 제공하며, 마이크로어레이 이미지 분석용 소프트웨어인 ArrayMall[1,2]과 유전자 조절 네트워크 분석 시스템인 GENAW[3]를 통합하고 마이크로어레이 실험데이터의 분석, 관리 및 데이터 공유를 위한 분산 시스템인 SMILE[4]에 대해 소개한다.

• Molecular & Cellular Toxicology
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• v.5 no.1
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• pp.32-43
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• 2009

Acetaminophen (APAP) overdose is known to cause severe hepatotoxicity mainly through the depletion of glutathione. In this study, we compared the cytotoxic effects of APAP on both a normal murine hepatic cell line, BNL CL.2, and its SV40-transformed cell line, BNL SV A.8. Gene expression profiles for APAP-treated cells were also obtained using microarray and analyzed to identify differences in genes or profiles that may explain the differences of susceptibility to APAP in these cell lines. These two cell lines exhibited different susceptibilities to APAP (0-$5,000{\mu}M$); BNL SV A.8 cells were more susceptible to APAP treatment compared to BNL CL.2 cells. A dose of $625{\mu}M$ APAP, which produced significant differences in cytotoxicity in these cell lines, was tested. Microarray analysis was performed to identify significant differentially expressed genes (DEGs) irrespective of APAP treatment. Genes up-regulated in BNL SV A.8 cells were associated with immune response, defense response, and apoptosis, while down-regulated genes were associated with catalytic activity, cell adhesion and the cytochrome P450 family. Consistent with the cytotoxicity data, no significant DEGs were found in BNL CL.2 cells after treatment with $625{\mu}M$ APAP, while cell cycle arrest and apoptosis-related genes were up-regulated in BNL SV A.8 cells. Based on the significant fold-changes in their expression, a genes were selected and their expressions were confirmed by quantitative real-time RT-PCR; there was a high correlation between them. These results suggest that gene expression profiles may provide a useful method for evaluating drug sensitivity of cell lines and eliciting the underlying molecular mechanism. We further compared the genes identified from our current in vitro studies to the genes previously identified in our lab as regulated by APAP in both C57BL/6 and ICR mice in vivo. We found that a few genes are regulated in a similar pattern both in vivo and in vitro. These genes might be useful to develop as in vitro biomarkers for predicting in vivo hepatotoxicity. Based on our results, we suggest that gene expression profiles may provide useful information for elucidating the underlying molecular mechanisms of drug susceptibility and for evaluating drug sensitivity in vitro for extrapolation to in vivo.

• Molecular & Cellular Toxicology
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• v.3 no.2
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• pp.119-126
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• 2007

1, 1-dichloroethylene (DCE) is well known hepatotoxicant as a model acute hepatotoxicity and selectively injure the bile canalicular membrane of centrilobular hepatocytes. In this study, we investigated hepatic gene expression and histopathological changes in response to DCE treatment. DCE was administered once daily at 20 mg/kg up to 14 days via intraperitoneal injection. Five mice were used in each test group and were sacrificed at 1, 7, and 14 days. Serum biochemical and histopathological analysis were performed for evaluation of hepatotoxicity level. Direct bilirubin and total bilirubin activities were slightly elevated in treated group at 7 days. DCE treatment for 7 days resulted in centrilobular hepatocyte hypertrophy and hepatocyte vacuolation, and mild hepatocyte vacuolation and high hepatocyte basophilia were observed in 14 days treated group. One hundred twenty three up-regulated genes and 445 down-regulated genes with over 2-fold changes between treated and control group at each time point were used for pathway analysis. These data may contribute in understanding the molecular mechanism DCE-induced hepatotoxicity.

• Reproductive and Developmental Biology
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• v.37 no.4
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• pp.185-192
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• 2013

Many countries have implemented genetic evaluation for fertility traits in recent years. In particular, reproductive trait is a complex trait and need to require a system-level approach for identifying candidate genes related to the trait. To find the candidate gene associated with reproductive trait, we applied a weighted gene co-expression network analysis from expression value of bovine genes. We identified three co-expressed modules associated with reproductive trait from bovine microarray data. Hub genes (ZP4, FHL2 and EGR4) were determined in each module; they were topologically centered with statistically significant value in the gene co-expression network. We were able to find the highly co-expressed gene pairs with a correlation coefficient. Finally, the crucial functions of co-expressed modules were reported from functional enrichment analysis. We suggest that the network-based approach in livestock may an important method for analyzing the complex effects of candidate genes associated with economic traits like reproduction.

• Genomics & Informatics
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• v.15 no.2
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• pp.56-64
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• 2017

We have previously reported that NS-398, a cyclooxygenase-2 (COX-2)-selective inhibitor, inhibited replicative cellular senescence in human dermal fibroblasts and skin aging in hairless mice. In contrast, celecoxib, another COX-2-selective inhibitor, and aspirin, a non-selective COX inhibitor, accelerated the senescence and aging. To figure out causal factors for the senescence-modulating effect of the inhibitors, we here performed cDNA microarray experiment and subsequent Gene Set Enrichment Analysis. The data showed that several senescence-related gene sets were regulated by the inhibitor treatment. NS-398 up-regulated gene sets involved in the tumor necrosis factor ${\beta}$ receptor pathway and the fructose and mannose metabolism, whereas it down-regulated a gene set involved in protein secretion. Celecoxib up-regulated gene sets involved in G2M checkpoint and E2F targets. Aspirin up-regulated the gene set involved in protein secretion, and down-regulated gene sets involved in RNA transcription. These results suggest that COX inhibitors modulate cellular senescence by different mechanisms and will provide useful information to understand senescence-modulating mechanisms of COX inhibitors.

• Korean Journal of Biological Psychiatry
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• v.12 no.1
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• pp.42-61
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• 2005

Objectives:The ginsenoside Rg1 and Rb1, the major components of ginseng saponin, have neurotrophic and neuroprotective effects including promotion of neuronal survival and proliferation, facilitation of learning and memory, and protection from ischemic injury and apoptosis. In this study, to investigate the molecular basis of the effects of ginsenoside on neuron, we analyzed gene expression profiling of SH-SY5Y human neuroblastoma cells treated with ginsenoside Rg1 or Rb1. Methods:SH-SY5Y cells were cultured and treated in triplicate with ginsenoside Rg1 or Rb1($80{\mu}M$, $40{\mu}M$, $20{\mu}M$). The proliferation rates of SH-SY5Y cells were determined by MTT assay and microscopic examination. We used a high density cDNA microarray chip that contained 8K human genes to analyze the gene expression profiles in SH-SY5Y cells. We analyzed using the Significance Analysis of Microarray(SAM) method for identifying genes on a microarray with statistically significant changes in expression. Results:Treatment of SH-SY5Y cells with $80{\mu}M$ ginsenoside Rg1 or Rb1 for 36h showed maximal proliferation compared with other concentrations or control. The results of the microarray experiment yielded 96 genes were upregulated(${\geq}$3 fold) in Rg1 treated cells and 40 genes were up-regulated(${\geq}$2 fold) in Rb1 treated cells. Treatment with ginsenoside Rg1 for 36h induced the expression of some genes associated with protein biosynthesis, regulation of transcription or translation, cell proliferation and growth, neurogenesis and differentiation, regulation of cell cycle, energy transport and others. Genes associated with neurogenesis and neuronal differentiation such as SCG10 and MLP increased in ginsenoside Rg1 treated cells, but such changes did not occur in Rb1-group. Conclusion:Our data provide novel insights into the gene mechanisms involved in possible role for ginsenoside Rg1 or Rb1 in mediating neuronal proliferation or cell viability, which can elicit distinct patterns of gene expression in neuronal cell line. Ginsenoside Rg1 have more broad and strong effects than ginsenoside Rb1 in gene expression and related cellular physiology. In addition, we suggest that SCG10 gene, which is known to be expressed in neuronal differentiation during development and neuronal regeneration during adulthood, may have a role in enhancement of activity dependent synaptic plasticity or cytoskeletal regulation following treatment of ginsenoside Rg1. Further, ginsenoside Rg1 may have a possible role in regeneration of injured neuron, promotion of memory, and prevention from aging or neuronal degeneration.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1003-1008
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• 2016

Breast cancer is now the leading cause of cancer death in women worldwide. Cancer progression is driven not only by cancer cell intrinsic alterations and interactions with tumor microenvironment, but also by systemic effects. Integration of multiple profiling data may provide insights into the underlying molecular mechanisms of complex systemic processes. We performed a bioinformatic analysis of two public available microarray datasets for breast tumor stroma and peripheral blood mononuclear cells, featuring integrated transcriptomics data, protein-protein interactions (PPIs) and protein subcellular localization, to identify genes and biological pathways that contribute to dialogue between tumor stroma and the peripheral circulation. Genes of the integrin family as well as CXCR4 proved to be hub nodes of the crosstalk network and may play an important role in response to stroma-derived chemoattractants. This study pointed to potential for development of therapeutic strategies that target systemic signals travelling through the circulation and interdict tumor cell recruitment.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.575-580
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• 2011

With the increasing expectation on personalized medicine, it is getting importance to analyze medical information in molecular biology perspective. Gene expression data are one of representative ones to show the microscopic phenomena of biological activities. In gene expression data analysis, one of major concerns is to identify markers which can be used to predict disease occurrence, progression or recurrence in the molecular level. Existing markers candidate identification methods mainly depend on statistical hypothesis test methods. This paper proposes a search method based decision tree induction to identify candidate markers which consist of multiple genes. The propose method discretizes numeric expression level into three categorical values and allows candidate markers' genes to be expressed by their negation as well as categorical values. It is desirable to have some number of genes to be included in markers. Hence the method is devised to try to find candidate markers with restricted number of genes.