• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2016년도 춘계 종합학술대회 논문집
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• pp.191-192
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• 2016

DNA 염기서열 자체에는 변화가 없으나 크로마틴의 변형을 통하여 유전자의 발현 양상이 변하는 현상을 후성유전이라 한다. 최근에 이런 후성유전학적 변이가 암 발생과 밀접한 연관이 있는 것으로 알려졌다. 본 연구에서는 암 관련 단백질과 암 관련 후성유전 단백질 상호작용 네트워크를 통하여 암과 후성 유전적 관계를 분석하고자 하였다. 먼저 상호작용 네트워크를 기반으로 허브에 해당하는 히스톤 변형 단백질 20개를 추출하였다. 추출한 20개 단백질을 KEGG pathway에 적용하여 암 관련 단백질과의 상관관계를 분석하였다. 암 관련 단백질 발현양상을 확인할 수 있는 Expression Atlas로부터 발현이 증가하거나 감소하는 단백질을 분류하고, 발현 정보를 KEGG pathway 위에 있는 단백질에 적용함으로써 후성유전학적 암 발생 기전을 도출하였다.

• Genomics & Informatics
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• 제6권3호
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• pp.147-152
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• 2008

The basic graph layout technique, one of many visualization techniques, deals with the problem of positioning vertices in a way to maximize some measure of desirability in a graph. The technique is becoming critically important for further development of the field of systems biology. However, applying the appropriate automatic graph layout techniques to the genomic scale flow of metabolism requires an understanding of the characteristics and patterns of duplicate and shared vertices, which is crucial for bioinformatics software developers. In this paper, we provide the results of parsing KEGG XML files from a graph-theoretical perspective, for future research in the area of automatic layout techniques in biological pathway domains.

• 한국정보과학회논문지:데이타베이스
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• 제32권2호
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• pp.120-128
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• 2005

최근 주요 생물정보학 데이타베이스 중 DDBJ, ENSEMBL, KEGG, 등의 데이타베이스는 연구자들의 편의를 위해 데이타와 분석용 도구들을 웹 서비스를 이용하여 제공한다. 이와 같이 웹 서비스를 이용하여 서비스를 제공하기 위해서는 SOAP 서버 객체와 메소드 정의가 매우 중요하다. 이 연구에서는 BIND, MINT, DIP과 같은 유전자 상호작용 데이타베이스를 위해서 필요한 SOAP 서버 객체에 대한 요구사항을 도출한다. 이어서 이 요구사항을 만족하는 SOAP 서버 객체와 메소드를 정의하였다. 이를 기반으로 프로토타입을 설계하고 구현한 것에 대하여 기술한다.

• Genomics & Informatics
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• 제8권2호
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• pp.94-96
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• 2010

Integrating various pathway data collections to create new biological knowledge is a challenge, for which novel computational tools play a key role. For this purpose, we developed the Java-based conversion modules KGML2SBML and KGML2BioPAX to translate KGML (KEGG Markup Language) into a couple of common data exchange formats: SBML (Systems Biology Markup Language) and BioPAX (Biological Pathway Exchange). We hope that our work will be beneficial for other Java developers when they extend their bioinformatics system into SBML- or BioPAX-aware analysis tools. This is part of our ongoing effort to develop an ultimate KEGG-based pathway enrichment analysis system.

• 한국컴퓨터정보학회논문지
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• 제14권5호
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• pp.175-182
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• 2009

Yeast를 이용하여 Two-Hybrid System 실험을 통해 밝혀진 단백질 상호작용 데이터에 단백질 위치 정보를 이용하여 가중치를 부여하고 단백질 신호 전달 경로를 추출하였다. 그 결과 중 MAPK Hypotonic Shock 기능의 데이터를 가지고 KEGG에서 제공하는 신호전달 경로와 비교하여 어느 정도 일치하는지의 유사도를 측정하고 시뮬레이션 하였다. 이때 프로세스 실행 시간도 측정하여 제시하였다. 향후 연구를 발전시키면 다양한 유전적 질병의 원인과 치료제 개발의 단서를 제공할 수 도 있으며 더 나아가 신약 개발을 할 수 있다.

• 대한한의학회지
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• 제31권4호
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• pp.79-100
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• 2010

Objective: Production of ROS from glucose toxicity results in injury of pancreatic $\beta$-cells in diabetes models. This study was undertaken to examine the influence of Lespedeza Cuneata extract (LCE) on cytoprotective effects on glucose toxicity, insulin secretion and gene expression in RIN-m5F cells. Methods: First, we measured LCE's antioxidant activity by DPPH free radical-scavenging activity and SOD activity. After the various concentrations of LCE were added to the RIN-m5F cells, we measured cell viability with glucose stimulation by MTT assay and glucose-stimulated insulin secretion. We analyzed gene expression with Agilent whole mouse genome 44K oligo DNA microarray and searched for related pathways in KEGG (Kyoto Encyclopedia of Genes and Genomes). Lastly we measured INS-1, INS-2, INS-R, IRS-1, IRS-2, IRS-3, GLP-1R, and GLP-2R mRNA expression by real time RT-PCR. Results: Free radical-scavenging activity, SOD activity and insulin secretion increased dependent on LCE concentration, but LCE did not show considerable cytoprotective effect on RIN-m5F cells. More than twice expressed gene was 6362 in Oligo DNA chip. In KEGG, the most related pathway was the metabolic pathway. In the insulin signaling pathway, up expressed genes were Irs1, Mapk8, Akt1, and Lipe and down expressed genes were Rhoq, Fbp2, Prkar2b, Gck, and Prkag1. In real time RT-PCR, IRS-2, and IRS-3 expression increased significantly compared to the control group on LCE $12{\mu}g/m{\ell}$ concentration and GCK expression decreased significantly compared to the control group. Conclusions: These results show that LCE encourages insulin secretion and insulin metabolism by complicated gene mechanisms. Further mechanism study and clinical study seem to be necessary about Lespedeza Cuneata.

• Molecular & Cellular Toxicology
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• 제3권3호
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• pp.208-213
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• 2007

With the help of a development and popularization of microarray technology that enable to us to simultaneously investigate the expression pattern of thousands of genes, the toxicogenomics experimenters can interpret the genome-scale interaction between genes exposed in toxicant or toxicant-related environment. The ultimate and primary goal of toxicogenomics identifies functional context among the group of genes that are differentially or similarly coexpressed under the specific toxic substance. On the other side, public reference databases with transcriptom, proteom, and biological pathway information are needed for the analysis of these complex omics data. However, due to the heterogeneous and independent nature of these databases, it is hard to individually analyze a large omics annotations and their pathway information. Fortunately, several web sites of the public database provide information linked to other. Nevertheless it involves not only approriate information but also unnecessary information to users. Therefore, the systematically integrated database that is suitable to a demand of experimenters is needed. For these reasons, we propose SOP (Search of Omics Pathway) database system which is constructed as the integrated biological database converting heterogeneous feature of public databases into combined feature. In addition, SOP offers user-friendly web interfaces which enable users to submit gene queries for biological interpretation of gene lists derived from omics experiments. Outputs of SOP web interface are supported as the omics annotation table and the visualized pathway maps of KEGG PATHWAY database. We believe that SOP will appear as a helpful tool to perform biological interpretation of genes or proteins traced to omics experiments, lead to new discoveries from their pathway analysis, and design new hypothesis for a next toxicogenomics experiments.

• Genomics & Informatics
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• 제20권2호
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• pp.20.1-20.13
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• 2022

Recent studies have focused on the early detection of ovarian cancer (OC) using tumor materials by liquid biopsy. The mechanisms of microRNAs (miRNAs) to impact OC and signaling pathways are still unknown. This study aims to reliably perform functional analysis of previously validated circulating miRNAs' target genes by using pathfindR. Also, overall survival and pathological stage analyses were evaluated with miRNAs' target genes which are common in the The Cancer Genome Atlas and GTEx datasets. Our previous studies have validated three downregulated miRNAs (hsa-miR-885-5p, hsa-miR-1909-5p, and hsa-let7d-3p) having a diagnostic value in OC patients' sera, with high-throughput techniques. The predicted target genes of these miRNAs were retrieved from the miRDB database (v6.0). Active-subnetwork-oriented Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted by pathfindR using the target genes. Enrichment of KEGG pathways assessed by the analysis of pathfindR indicated that 24 pathways were related to the target genes. Ubiquitin-mediated proteolysis, spliceosome and Notch signaling pathway were the top three pathways with the lowest p-values (p < 0.001). Ninety-three common genes were found to be differentially expressed (p < 0.05) in the datasets. No significant genes were found to be significant in the analysis of overall survival analyses, but 24 genes were found to be significant with pathological stages analysis (p < 0.05). The findings of our study provide in-silico evidence that validated circulating miRNAs' target genes and enriched pathways are related to OC and have potential roles in theranostics applications. Further experimental investigations are required to validate our results which will ultimately provide a new perspective for translational applications in OC management.

• 대한본초학회지
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• 제38권6호
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• pp.73-91
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• 2023

Objectives : This study used a network pharmacology approach to elucidate the efficacy and molecular mechanisms of Daehwangmokdanpitang (DHMDPT) on Psoriasis. Methods : Using OASIS databases and PubChem database, compounds of DHMDPT and their target genes were collected. The putative target genes of DHMDPT and known target genes of psoriasis were compared and found the correlation. Then, the network was constructed using Cytoscape 3.10.1. The key target genes were screened by Analyzer network and their functional enrichment analysis was conducted based on the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways to predict the mechanisms. Results : The result showed that total 30 compounds and 439 related genes were gathered from DHMDPT. 264 genes were interacted with psoriasis gene set, suggesting that the effects of DHMDPT are closely related to psoriasis. Based on GO enrichment analysis and KEGG pathways, 'Binding', 'Cytokine Activity', 'Receptor Ligand Activity' 'HIF-1 signaling pathway', 'IL-17 signaling pathway', 'Toll-like receptor signaling pathway', and 'TNF signaling pathway' were predicted as functional pathways of 16 key target genes of DHMDPT on psoriasis. Among the target genes, IL6, IL1B, TNF, AKT1 showed high correlation with the results of KEGG pathways. Additionally, Emodin, Acetovanillone, Gallic acid, and Ferulic acid showed a high relevance with key genes and their mechanisms. Conclusion : Through a network pharmacological method, DHMDPT was predicted to have high relevance with psoriasis. This study could be used as a basis for studying therapeutic effects of DHMDPT on psoriasis.

• 한국콘텐츠학회논문지
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• 제14권11호
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• pp.467-475
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• 2014

최근 유전체학의 발전, 웨어러블 디바이스의 확산, IT/NT의 발전 등에 따라 방대한 양의 바이오-메디컬 데이터가 생산되고, 이에 따라 빅데이터를 활용한 헬스케어 산업이 급속히 발달하고 있으며, 이와 관련된 빅데이터 기술은 국민의 건강 증대와 건강한 고령 삶을 제공하는 핵심 기술로 급부상하고 있다. 패스웨이(Pathway)는 단백질, 유전자, 세포 등의 생체적 요소 간의 역학관계 혹은 상호작용 등을 네트워크 형식으로 표현한 생물학적 심층지식으로, 바이오-메디컬 빅데이터 분석에 있어서 널리 활용되고 있다. 하지만 패스웨이는 매우 다양한 형태를 갖고 용량이 매우 큰 빅데이터로 이를 분석하는데 많은 시간이 소요되며, 현재까지도 다양한 패스웨이를 통합 분석할 수 있는 시스템은 전무하다. 그래서 본 논문에서는 세계적으로 가장 우수하고 방대한 양의 패스웨이를 제공하는 KEGG 패스웨이 데이터베이스로부터 사용자가 관심 갖는 패스웨이만을 자동 수집하고 패스웨이 간 계층구조를 기반으로 네트워크를 구성 후, 해당 패스웨이 네트워크에 대한 클러스터링과 핵심 패스웨이 선정을 통해 패스웨이 간의 역학관계 또는 상호작용을 직관적으로 분석할 수 시스템을 제안했다. 마지막으로, 다양한 성능 평가 결과를 통해 개발한 분석 시스템의 우수성을 입증한다.