• 한국정보과학회논문지:소프트웨어및응용
• /
• 제34권5호
• /
• pp.389-396
• /
• 2007

서로 다른 종에서의 대사 경로를 비교하는 것은 아직 밝혀지지 않은 유전자를 찾는 문제에 있어 매우 중요하다. 많은 대사 경로 시각화가 제시되었지만 생물학자들은 대사 경로를 단순히 보는 것뿐만 아니라 비교하는 시각화를 필요로 한다. K-Viz는 KEGG 기반의 대사 경로를 위한 시각화 툴이다. 다른 종의 대사 경로를 비교하기 위해 KEGG의 PathComp와 같은 경로를 서로 다른 색으로 표현하는 방법과 각 종에서의 경로를 테이블로 보여준다. K-Viz는 생물학자들이 서로 다른 종에서의 대사 경로 비교를 이해하는데 도움을 준다.

• 생명과학회지
• /
• 제34권3호
• /
• pp.179-190
• /
• 2024

Canabas sativa L. (marijuana and hemp)는 전 세계적으로 널리 재배되는 식물로 식품, 의약품 등의 재료로 사용되었다. 본 연구는 네트워크 약리학을 이용하여 대마 줄기 및 뿌리 추출물의 기능적 효과를 예측하고 이들의 새로운 기능을 알아보고자 하였다. 줄기 및 뿌리 에탄올 추출물의 성분은 GC/MS로 확인하였고, 성분과 단백질 간의 네트워크는 STIHICI 데이터베이스를 이용하여 알아보았다. 성분과 연결된 단백질의 작용기전은 KEGG pathway 분석을 수행하였다. 추출물의 효과는 실시간 PCR을 이용하여 lysophosphatylcholine 유도 THP-1 세포에서 확인하였다. 줄기 및 뿌리 추출물에서 각각 21개 및 32개의 성분이 확인되었다. 줄기 및 뿌리의 성분과 연결된 단백질은 각각 147개, 184개의 단백질이었다. KEGG pathway 분석결과 MAPK signaling pathway를 포함한 69개의 경로가 추출물에 의해 공통적으로 영향을 받는 것으로 나타났다. 경로 네크워크를 이용한 추가 조사 결과, Terpenoid backbone biosynthesis 추출물 및 MVK와 MVD 의해 영향을 받을 가능성이 높으며, 유전자 발현은 추출물에 의해 LPC 유도 THP-1 세포에서 감소하였다. 따라서 본 연구에서는 대마 줄기 및 뿌리 에탄올 추출물이 다양한 경로로 영향을 미칠 수 있음을 보여주었고, 이러한 결과는 대마의 효과를 예측하고 연구하기 위한 기초 정보를 제공할 것으로 사료된다.

• Biomolecules & Therapeutics
• /
• 제30권1호
• /
• pp.98-116
• /
• 2022

The small GTPase RhoA has been studied extensively for its role in actin dynamics. In this study, multiple bioinformatics tools were applied cooperatively to the microarray dataset GSE64714 to explore previously unidentified functions of RhoA. Comparative gene expression analysis revealed 545 differentially expressed genes in RhoA-null cells versus controls. Gene set enrichment analysis (GSEA) was conducted with three gene set collections: (1) the hallmark, (2) the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and (3) the Gene Ontology Biological Process. GSEA results showed that RhoA is related strongly to diverse pathways: cell cycle/growth, DNA repair, metabolism, keratinization, response to fungus, and vesicular transport. These functions were verified by heatmap analysis, KEGG pathway diagramming, and direct acyclic graphing. The use of multiple gene set collections restricted the leakage of information extracted. However, gene sets from individual collections are heterogenous in gene element composition, number, and the contextual meaning embraced in names. Indeed, there was a limit to deriving functions with high accuracy and reliability simply from gene set names. The comparison of multiple gene set collections showed that although the gene sets had similar names, the gene elements were extremely heterogeneous. Thus, the type of collection chosen and the analytical context influence the interpretation of GSEA results. Nonetheless, the analyses of multiple collections made it possible to derive robust and consistent function identifications. This study confirmed several well-described roles of RhoA and revealed less explored functions, suggesting future research directions.

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

• 한국생물정보학회:학술대회논문집
• /
• 한국생물정보시스템생물학회 2000년도 International Symposium on Bioinformatics
• /
• pp.56-58
• /
• 2000

Post-genomics may be defined in different ways depending on how one views the challenges after the genome. A popular view is to follow the concept of the central dogma in molecular biology, namely from genome to transcriptome to proteome. Projects are going on to analyze gene expression profiles both at the mRNA and protein levels and to catalog protein 3D structure families, which will no doubt help the understanding of information in the genome. However complete, such catalogs of genes, RNAs, and proteins only tell us about the building blocks of life. They do not tell us much about the wiring (interaction) of building blocks, which is essential for uncovering systemic functional behaviors of the cell or the organism. Thus, an alternative view of post-genomics is to go up from the molecular level to the cellular level, and to understand, what I call, the "interactome"or a complete picture of molecular interactions in the cell. KEGG (http://www.genome.ad.jp/kegg/) is our attempt to computerize current knowledge on various cellular processes as a collection of "generalized"protein-protein interaction networks, to develop new graph-based algorithms for predicting such networks from the genome information, and to actually reconstruct the interactomes for all the completely sequenced genomes and some partial genomes. During the reconstruction process, it becomes readily apparent that certain pathways and molecular complexes are present or absent in each organism, indicating modular structures of the interactome. In addition, the reconstruction uncovers missing components in an otherwise complete pathway or complex, which may result from misannotation of the genome or misrepresentation of the KEGG pathway. When combined with additional experimental data on protein-protein interactions, such as by yeast two-hybrid systems, the reconstruction possibly uncovers unknown partners for a particular pathway or complex. Thus, the reconstruction is tightly coupled with the annotation of individual genes, which is maintained in the GENES database in KEGG. We are also trying to expand our literature surrey to include in the GENES database most up-to-date information about gene functions.

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

• Asian Pacific Journal of Cancer Prevention
• /
• 제16권5호
• /
• pp.1781-1787
• /
• 2015

Background: miRNAs are relatively recently discovered cancer biomarkers which have important implications for cancer early diagnosis, treatment and estimation of prognosis. Here we focussed on expression of mir-196a-5p in gastric cancer tissues and cell lines so as to analyse its significance for clinicopathologic characteristics and generate enriched KEGG pathways clustered by target genes for exploring its potential roles as a biomarker in gastric cancer. Materials and Methods: The expression of mir-196a-5p in poorly, moderate and well differentiated gastric cancer cell lines compared with GES-1 was detected by RT-qPCR, and the expression of mir-196a-5p in gastric cancer tissues comparing with adjacent non cancer tissues of 58 cases were also assessed by RT-qPCR. Subsequently, an analysis of clinical significance of mir-196a-5p in gastric cancer and enriched KEGG pathways was executed based on the miRWalk prediction database combined with bioinformatics tools DAVID 6.7 and Mirfocus 3.0. Results: RT-qPCR showed that mir-196a-5p was up-regulated in 6 poorly and moderate differentiated gastric cancer cell lines SGC-7901, MKN-45, MKN-28, MGC-803, BGC-823, HGC-27 compared with GES-1, but down-regulated in the highly differentiated gastric cancer cell line AGS. Clinical data indicated mir-196a-5p to beup-regulated in gastric cancer tissues (47/58). Overexpression of mir-196a-5p was associated with more extensive degree of lymph node metastasis and clinical stage (P < 0.05; x2 test). Enriched KEGG pathway analyses of predicted and validated targets in miRWalk combined with DAVID 6.7 and Mirfocus 3.0 showed that the targeted genes regulated by mir-196a-5p were involved in malignancy associated biology. Conclusions: Overexpression of mir-196a-5p is associated with lymph node metastasis and clinical stage, and enriched KEGG pathway analyses showed that targeted genes regulated by mir-196a-5p may contribute to tumorgenesis, suggesting roles as an oncogenic miRNA biomarker in gastric cancer.

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

• Genomics & Informatics
• /
• 제8권2호
• /
• pp.94-96
• /
• 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
• /
• 제14권5호
• /
• pp.175-182
• /
• 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.