• Title/Summary/Keyword: KEGG

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Correlation Between Protein-Protein Interaction Network and KEGG Path Flow Network (단백질 상호작용 네트워크와 KEGG경로 흐름 네트워크의 비교)

  • Cho, Sung Jin;Kim, Hak Yong
    • Proceedings of the Korea Contents Association Conference
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    • 2011.05a
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    • pp.347-348
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    • 2011
  • 단백질 상호작용 네트워크에 대한 분석은 거시적인 생물학적 현상을 이해하는 하나의 수단으로써 보편적인 연구방법으로 활용하고 있다. 매우 복잡한 단백질 상호작용 네트워크로부터 유용한 정보를 도출하는 연구의 일환으로 우리는 단백질 네트워크에 있는 단백질들이 KEGG 경로에 있는 생체대사와의 연관성을 분석하였다. 여기서 구축된 네트워크를 KEGG 경로 흐름 네트워크로 명명하고 두 네트워크 사이의 연관성을 분석하였다. 이를 위해 피루브산 탈수소 효소 및 알파-케토글루탐산 탈수소 효소 2차 상호작용 네트워크의 전체 단백질 목록을 기반으로 각각의 KEGG 경로들을 추출하였다. 각 KEGG 경로들에 나타난 단백질들을 통해 KEGG 경로 흐름 네트워크를 구축하였고 이 흐름 네트워크에 포함된 단백질의 분류를 통하여 유용한 정보를 추출하였다.

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K-Viz: KEGG Based Bisualization for Comparing Metabolic Pathways (K-Viz : 대사 경로 비교를 위한 KEGG 기반의 시각화)

  • Im, Dong-Hyuk;Lee, Dong-Hee;Kim, Hyoung-Joo
    • Journal of KIISE:Software and Applications
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    • v.34 no.5
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    • pp.389-396
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    • 2007
  • The comparison of metabolic pathway in different species is important in detecting a missing gene. There are many visualizations for metabolic pathway. However, Biologists need not only a simple path but also a visualization for comparison. K-Viz is a tool for visualization of metabolic pathway based on KEGG. To compare pathways in different species, K-Viz uses different color for path such as PathComp in KEGG and shows the table of path in pathway. K-Viz helps biologists to understand the comparison of metabolic pathways in different species.

Gene annotation by the "interactome"analysis in KEGG

  • Kanehisa, Minoru
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2000.11a
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    • pp.56-58
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    • 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.

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Clinical Significance of Upregulation of mir-196a-5p in Gastric Cancer and Enriched KEGG Pathway Analysis of Target Genes

  • Li, Hai-Long;Xie, Shou-Pin;Yang, Ya-Li;Cheng, Ying-Xia;Zhang, Ying;Wang, Jing;Wang, Yong;Liu, Da-Long;Chen, Zhao-Feng;Zhou, Yong-Ning;Wu, Hong-Yan
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.5
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    • pp.1781-1787
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    • 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.

Implementing System for Dynamic Constructing and Clustering on KEGG Pathway Network (KEGG 패스웨이 네트워크 동적 구축 및 클러스터링 시스템 개발)

  • Seo, Dongmin;Lee, Min-Ho;Yu, Seok Jong
    • Proceedings of the Korea Contents Association Conference
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    • 2015.05a
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    • pp.231-232
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    • 2015
  • 최근 유전체학, NGS(Next Generation Sequencing) 기술, IT/NT 장비의 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. 패스웨이는 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 소요된다. 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.

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In silico analysis of MeJA-induced comparative transcriptomes in Brassica oleraceae L. var. capitata

  • Lee, Ok Ran;Kim, Dae-Soo
    • Journal of Plant Biotechnology
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    • v.43 no.2
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    • pp.189-203
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    • 2016
  • Brassica oleraceae var capitata is a member of the Brassicaceae family and is widely used as an horticultural crop. In the present study, transcriptome analysis of B. oleraceae L. var capitata was done for the first time using eight-week old seedlings treated with $50{\mu}m$ MeJA, versus mock-treated samples. The complete transcripts for both samples were obtained using the GS-FLX sequencer. Overall, we obtained 275,570 and 266,457 reads from seedlings treated with or without $50{\mu}m$ MeJA, respectively. All the obtained reads were annotated using biological databases and functionally classified using gene ontology (GO), the Kyoto Encyclopedia of Genes and Genomics (KEGG). By using GO analyses, putative transcripts were examined in terms of biotic and abiotic stresses, cellular component organization, biogenesis, and secondary metabolic processes. The KEGG pathways for most of the transcripts were involved in carbohydrate metabolism, energy metabolism, and secondary metabolite synthesis. In order to double the sequenced data, we randomly chose two putative genes involved in terpene biosynthetic pathways and studied their transcript patterns under MeJA treatment. This study will provide us a platform to further characterize the genes in B. oleracea var capitata.

Discovery of Cellular RhoA Functions by the Integrated Application of Gene Set Enrichment Analysis

  • Chun, Kwang-Hoon
    • Biomolecules & Therapeutics
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    • v.30 no.1
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    • pp.98-116
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    • 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.

A Study of the Predictive Effectiveness of Stem and Root Extracts of Cannabis sativa L. Through Network Pharmacological Analysis (네트워크 분석기반을 통한 대마 줄기 및 뿌리 추출물의 약리효능 예측연구)

  • Myung-Ja Shin;Min-Ho Cha
    • Journal of Life Science
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    • v.34 no.3
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    • pp.179-190
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    • 2024
  • Cannabis sativa is a plant widely cultivated worldwide and has been used as a material for food, medicine, building materials and cosmetics. In this study, we assessed the functional effects of C. sativa stem and root extracts using network pharmacology and confirmed their novel functions. The components in stem and root ethanol extracts were identified by gas chromatography-mass spectrometry analysis, and networks between the components and proteins were constructed using the STICHI database. Functional annotation of the proteins was performed using the KEGG pathway. The effects of the extracts were confirmed in lysophosphatidylcholine-induced THP-1 cells using real-time PCR. A total of 21 and 32 components were identified in stem and root extracts, respectively, and 147 and 184 proteins were linked to stem and root components, respectively. KEGG pathway analysis showed that 69 pathways, including the MAPK signaling pathway, were commonly affected by the extracts. Further investigation using pathway networks revealed that terpenoid backbone biosynthesis was likely affected by the extracts, and the expression of the MVK and MVD genes, key proteins in terpenoid backbone biosynthesis, was decreased in LPC-induced THP-1 cells. Therefore, this study determined the diverse function of C. sativa extracts, providing information for predicting and researching the effects of C. sativa.

Genomic Tree of Gene Contents Based on Functional Groups of KEGG Orthology

  • Kim Jin-Sik;Lee Sang-Yup
    • Journal of Microbiology and Biotechnology
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    • v.16 no.5
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    • pp.748-756
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    • 2006
  • We propose a genome-scale clustering approach to identify whole genome relationships using the functional groups given by the Kyoto Encyclopedia of Genes and Genomes Orthology (KO) database. The metabolic capabilities of each organism were defined by the number of genes in each functional category. The archaeal, bacterial, and eukaryotic genomes were compared by simultaneously applying a two-step clustering method, comprised of a self-organizing tree algorithm followed by unsupervised hierarchical clustering. The clustering results were consistent with various phenotypic characteristics of the organisms analyzed and, additionally, showed a different aspect of the relationship between genomes that have previously been established through rRNA-based comparisons. The proposed approach to collect and cluster the metabolic functional capabilities of organisms should make it a useful tool in predicting relationships among organisms.

Selection of optimal protein domains for DNA repair inhibition in cancer cells based on bioinformatics (생물정보학 기반 암세포 내 DNA 복구 저해를 위한 최적 단백질 도메인 선정)

  • Jo, Si Hyang;Kim, Hak Yong
    • Proceedings of the Korea Contents Association Conference
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    • 2016.05a
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    • pp.185-186
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    • 2016
  • 최근 DNA 복구 기작 저해가 암 전이를 억제한다는 연구결과가 발표되었다. 이번 연구에서는 DNA 복구 기작을 효율적으로 저해시킬 수 있는 단백질을 선정하고자 했다. 먼저 HPRD에서 59개의 DNA repair 단백질 정보를 얻고 각각의 도메인 정보를 추출하였다. 이 단백질과 상호작용하는 단백질을 KEGG로 부터 추출하고 추출한 단백질의 도메인 정보는 HPRD에서 얻었다. Cytoscape를 통하여 DNA 복구 단백질-상호작용 단백질-도메인의 네트워크를 시각화하였다. 네트워크 상에서 보존적이며 핵심적인 단백질 후보 및 도메인 후보를 선정 하였다. KEGG에서 제공하는 암의 경로(pathways in cancer)을 이용하여 후보의 적용 가능성을 확인하였다. 선정한 최종 후보들은 향후 암 전이 억제에 사용될 수 있는 타깃이 될 수 있을 것으로 기대한다.

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