• 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.

• 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.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.467-475
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• 2014

With the development of genomics, wearable device and IT/NT, a vast amount of bio-medical data are generated recently. Also, healthcare industries based on big-data are booming and big-data technology based on bio-medical data is rising rapidly as a core technology for improving the national health and aged society. A pathway is the biological deep knowledge that represents the relations of dynamics and interaction among proteins, genes and cells by a network. A pathway is wildly being used as an important part of a bio-medical big-data analysis. However, a pathway analysis requires a lot of time and effort because a pathway is very diverse and high volume. Also, multidimensional analysis systems for various pathways are nonexistent even now. In this paper, we proposed a pathway analysis system that collects user interest pathways from KEGG pathway database that supports the most widely used pathways, constructs a network based on a hierarchy structure of pathways and analyzes the relations of dynamics and interaction among pathways by clustering and selecting core pathways from the network. Finally, to verify the superiority of our pathway analysis system, we evaluate the performance of our system in various experiments.

• Molecular & Cellular Toxicology
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• v.3 no.3
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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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• v.8 no.2
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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.

• 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.

• 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.

• Molecular & Cellular Toxicology
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• v.4 no.4
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• pp.267-277
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• 2008

Benzene and ethylbenzene (BE), the volatile organic compounds (VOCs) are common constituents of cleaning and degreasing agents, paints, pesticides, personal care products, gasoline and solvents. VOCs are evaporated at room temperature and most of them exhibit acute and chronic toxicity to human. Chronic exposure of benzene is responsible for myeloid leukemia and also ethylbenzene is also recognized as a possible carcinogen. To evaluate the BE effect on human, whole human genome 35 K oligonucleotide microarray were screened for the identification of the differential expression profiling. We identified 280 up-regulated and 201 down-regulated genes changed by more than 1.5 fold by BE exposure. Functional analysis was carried out by using DAVID bioinformatics software. Clustering of these differentially expressed genes were associated with immune response, cytokine-cytokine receptor interaction, toll-like signaling pathway, small cell lung cancer, immune response, apoptosis, p53 signaling pathway and MAPKKK cascade possibly constituting alternative or subordinate pathways of hematotoxicity and immune toxicity. Gene ontology analysis methods including biological process, cellular components, molecular function and KEGG pathway thus provide a fundamental basis of the molecular pathways through BEs exposure in human lymphoma cells. This may provides a valuable information to do further analysis to explore the mechanism of BE induced hematotoxicity.

• The Korea Journal of Herbology
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• v.38 no.6
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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.

• Genomics & Informatics
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• v.20 no.2
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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.