• Title/Summary/Keyword: Gene Database

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Quantitative Analysis of 1-Deoxynojirimycin Content Using Silkworm Genetic Resources

  • Ju, Wan-Taek;Kim, Kee-Young;Sung, Gyoo-Byung;Kim, Yong-Soon
    • International Journal of Industrial Entomology and Biomaterials
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    • v.29 no.2
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    • pp.162-168
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    • 2014
  • 1-Deoxynojirimycin(1-DNJ or DNJ), a component in silkworm powder, prevents glucose from being absorbed into the bloodstream from the small intestine by inhibiting ${\alpha}$-glucosidase activity. This study compared the functional components of 1-DNJ from various silkworm species using a gene database with those of 1-DNJ produced by silkworms bred through cross-combinations. We utilized comparisons of geographical origins and species of silkworms using a gene database and discovered that 1-DNJ activity was ranked in the following order by species, Japanese (SK-1) > Chinese (C48) > European (Rock191). 1-DNJ constituted varying percentages of silkworm organs in the following order, blood > epithelial tissue > body fat > silk glands. With regard to sex, 1-DNJ, levels were higher in males than females. However, 1-DNJ levels with respect to various genetic traits (blood color, silk color, and egg color) were consistent. In order to study 1-DNJ changes that occurred during cross breeding of the silkworm gene, we bred cross-combinations utilizing SK-1 and C48 silkworms. In conclusion, in order to provide information about the constituents of functional materials contained in silkworm powder, it is imperative that silkworm cross breeding occurs so that the database of functional materials extracted from silkworms will expand.

Systems Pharmacological Analysis of Dichroae Radix in Anti-Tumor Metastasis Activity (시스템 약리학적 분석에 의한 상산의 암전이 억제 효과)

  • Jee Ye Lee;Ah Yeon Shin;Hak Koon Kim;Won Gun An
    • Herbal Formula Science
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    • v.31 no.4
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    • pp.295-313
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    • 2023
  • Objectives : While treatments for cancer are advancing, the development of effective treatments for cancer metastasis, the main cause of cancer patient death, remains insufficient. Recent studies on Dichroae Radix have revealed that its active ingredients have the potential to inhibit cancer metastasis. This study aimed to investigate the cancer metastasis inhibitory effect of Dichroae Radix using network pharmacological analysis. Methods : The active compounds of Dichroae Radix have been identified using Traditional Chinese Medicine System Pharmacology Database and Analysis Platform. The UniProt database was used to collect each of information of all target proteins associated with the active compounds. To find the bio-metabolic processes associated with each target, the DAVID6.8 Gene Functional classifier tool was used. Compound-Target and Target-Pathway networks were analyzed via Cytoscape 3.40. Results : In total, 25 active compounds and their 62 non-redundant targets were selected through the TCMSP database and analysis platform. The target genes underwent gene ontology and pathway enrichment analysis. The gene list applied to the gene ontology analysis revealed associations with various biological processes, including signal transduction, chemical synaptic transmission, G-protein-coupled receptor signaling pathways, response to xenobiotic stimulus, and response to drugs, among others. A total of eleven genes, including HSP90AB1, CALM1, F2, AR, PAKACA, PTGS2, NOS2, RXRA, ESR1, ESR2, and NCOA1, were found to be associated with biological pathways related to cancer metastasis. Furthermore, nineteen of the active compounds from Dichroae Radix were confirmed to interact with these genes. Conclusions : The results provide valuable insights into the mechanism of action and molecular targets of Dichroae Radix. Notably, Berberine, the main active ingredient of Dichroae Radix, plays a significant role in degrading AR proteins in advanced prostate cancer. Further studies and validations can provide crucial data to advance cancer metastasis prevention and treatment strategies.

Construction of Gene Network System Associated with Economic Traits in Cattle (소의 경제형질 관련 유전자 네트워크 분석 시스템 구축)

  • Lim, Dajeong;Kim, Hyung-Yong;Cho, Yong-Min;Chai, Han-Ha;Park, Jong-Eun;Lim, Kyu-Sang;Lee, Seung-Su
    • Journal of Life Science
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    • v.26 no.8
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    • pp.904-910
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    • 2016
  • Complex traits are determined by the combined effects of many loci and are affected by gene networks or biological pathways. Systems biology approaches have an important role in the identification of candidate genes related to complex diseases or traits at the system level. The gene network analysis has been performed by diverse types of methods such as gene co-expression, gene regulatory relationships, protein-protein interaction (PPI) and genetic networks. Moreover, the network-based methods were described for predicting gene functions such as graph theoretic method, neighborhood counting based methods and weighted function. However, there are a limited number of researches in livestock. The present study systemically analyzed genes associated with 102 types of economic traits based on the Animal Trait Ontology (ATO) and identified their relationships based on the gene co-expression network and PPI network in cattle. Then, we constructed the two types of gene network databases and network visualization system (http://www.nabc.go.kr/cg). We used a gene co-expression network analysis from the bovine expression value of bovine genes to generate gene co-expression network. PPI network was constructed from Human protein reference database based on the orthologous relationship between human and cattle. Finally, candidate genes and their network relationships were identified in each trait. They were typologically centered with large degree and betweenness centrality (BC) value in the gene network. The ontle program was applied to generate the database and to visualize the gene network results. This information would serve as valuable resources for exploiting genomic functions that influence economically and agriculturally important traits in cattle.

Identification of novel potential drugs and miRNAs biomarkers in lung cancer based on gene co-expression network analysis

  • Sara Hajipour;Sayed Mostafa Hosseini;Shiva Irani;Mahmood Tavallaie
    • Genomics & Informatics
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    • v.21 no.3
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    • pp.38.1-38.8
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    • 2023
  • Non-small cell lung cancer (NSCLC) is an important cause of cancer-associated deaths worldwide. Therefore, the exact molecular mechanisms of NSCLC are unidentified. The present investigation aims to identify the miRNAs with predictive value in NSCLC. The two datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DEmiRNA) and mRNAs (DEmRNA) were selected from the normalized data. Next, miRNA-mRNA interactions were determined. Then, co-expression network analysis was completed using the WGCNA package in R software. The co-expression network between DEmiRNAs and DEmRNAs was calculated to prioritize the miRNAs. Next, the enrichment analysis was performed for DEmiRNA and DEmRNA. Finally, the drug-gene interaction network was constructed by importing the gene list to dgidb database. A total of 3,033 differentially expressed genes and 58 DEmiRNA were recognized from two datasets. The co-expression network analysis was utilized to build a gene co- expression network. Next, four modules were selected based on the Zsummary score. In the next step, a bipartite miRNA-gene network was constructed and hub miRNAs (let-7a-2-3p, let-7d-5p, let-7b-5p, let-7a-5p, and let-7b-3p) were selected. Finally, a drug-gene network was constructed while SUNITINIB, MEDROXYPROGESTERONE ACETATE, DOFETILIDE, HALOPERIDOL, and CALCITRIOL drugs were recognized as a beneficial drug in NSCLC. The hub miRNAs and repurposed drugs may act a vital role in NSCLC progression and treatment, respectively; however, these results must validate in further clinical and experimental assessments.

Systemic Analysis of Antibacterial and Pharmacological Functions of Anisi Stellati Fructus (대회향의 시스템 약리학적 분석과 항균작용)

  • Han, Jeong A;Choo, Ji Eun;Shon, Jee Won;Kim, Youn Sook;Suh, Su Yeon;An, Won Gun
    • Journal of Life Science
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    • v.29 no.2
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    • pp.181-190
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    • 2019
  • The purpose of this study was to acquire the active compounds of Anisi stellati fructus (ASF) and to analyze the genes and diseases it targets, focusing on its antibacterial effects using a system pharmacological analysis approach. Active compounds of ASF were obtained through the Traditional Chinese Medicine Systems Pharmacology (TCMSP) Database and Analysis Platform. This contains the pharmacokinetic properties of active compounds and related drug-target-disease networks, which is a breakthrough in silico approach possible at the network level. Gene information of targets was gathered from the UnitProt Database, and gene ontology analysis was performed using the David 6.8 Gene Functional Classification Tool. A total of 201 target genes were collected, which corresponded to the nine screened active compounds, and 47 genes were found to act on biological processes related to antimicrobial activity. The representative active compounds involved in antibacterial action were luteolin, kaempferol, and quercetin. Among their targets, Chemokine ligand2, Interleukin-10, Interleukin-6, and Tumor Necrosis Factor were associated with more than three antimicrobial biological processes. This study has provided accurate evidence while saving time and effort to select future laboratory research materials. The data obtained has provided important data for infection prevention and treatment strategies.

Constructing Gene Regulatory Networks using Temporal Relation Rules from 3-Dimensional Gene Expression Data (3차원 유전자 발현 데이터에서의 시간 관계 규칙을 이용한 유전자 상호작용 조절 네트워크 구축)

  • Meijing Li;Jin Hyoung Park;Heon Gyu Lee;Keun Ho Ryu
    • Proceedings of the Korea Information Processing Society Conference
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    • 2008.11a
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    • pp.340-343
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    • 2008
  • 유전자들은 복잡한 상호작용을 통해 세포의 기능이 조절된다. 상호작용하는 유전자 그룹들을 유전자 조절 네트워크라고 한다. 기존의 유전자 조절 네트워크는 2D microarray 데이터를 이용하여 시간의 흐름에 따른 유전자간의 상호작용을 알 수가 없었다. 이 논문에서는 시간의 변화에 따른 유전자들 간의 조절관계를 살펴 볼 수 있는 조절네트워크 모델링의 방법을 제시한다. 유전자의 발현양을 표시하기 위해 이진 이산화 방법을 사용하였고 3D microarray 데이터에서 유전자 발현 패턴을 찾기 위해 Cube mining 알고리즘을 적용하였고, 유전자간의 관계를 밝히기 위해 시간 관계 규칙탐사 기법을 사용하여 유전자들 간의 시간 관계를 포함한 유전자 조절네트워크를 구축하였다. 이 연구는 시간의 흐름에 따른 유전자간의 상호작용을 알 수 있으며, 모델링된 조절 네트워크를 이용하여 기능이 아직 발견되지 않은 유전자들의 기능을 예측 할 수 있다.

Tag-SNP selection and online database construction for haplotype-based marker development in tomato (유전자 단위 haplotype을 대변하는 토마토 Tag-SNP 선발 및 웹 데이터베이스 구축)

  • Jeong, Hye-ri;Lee, Bo-Mi;Lee, Bong-Woo;Oh, Jae-Eun;Lee, Jeong-Hee;Kim, Ji-Eun;Jo, Sung-Hwan
    • Journal of Plant Biotechnology
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    • v.47 no.3
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    • pp.218-226
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    • 2020
  • This report describes methods for selecting informative single nucleotide polymorphisms (SNPs), and the development of an online Solanaceae genome database, using 234 tomato resequencing data entries deposited in the NCBI SRA database. The 126 accessions of Solanum lycopersicum, 68 accessions of Solanum lycopersicum var. cerasiforme, and 33 accessions of Solanum pimpinellifolium, which are frequently used for breeding, and some wild-species tomato accessions were included in the analysis. To select tag-SNPs, we identified 29,504,960 SNPs in 234 tomatoes and then separated the SNPs in the genic and intergenic regions according to gene annotation. All tag-SNP were selected from non-synonymous SNPs among the SNPs present in the gene region and, as a result, we obtained tag-SNP from 13,845 genes. When there were no non-synonymous SNPs in the gene, the genes were selected from synonymous SNPs. The total number of tag-SNPs selected was 27,539. To increase the usefulness of the information, a Solanaceae genome database website, TGsol (http://tgsol. seeders.co.kr/), was constructed to allow users to search for detailed information on resources, SNPs, haplotype, and tag-SNPs. The user can search the tag-SNP and flanking sequences for each gene by searching for a gene name or gene position through the genome browser. This website can be used to efficiently search for genes related to traits or to develop molecular markers.

Genes expression monitoring using cDNA microarray: Protocol and Application

  • Muramatsu Masa-aki
    • Proceedings of the Korean Society of Toxicology Conference
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    • 2000.11a
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    • pp.31-41
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    • 2000
  • The major issue in the post genome sequencing era is determination of gene expression patterns in variety of biological systems. A microarray system is a powerful technology for analyzing the expression profile of thousands of genes at one experiment. In this study, we constructed cDNA microarray which carries 2,304 cDNAS derived from oligo-capped mouse cDNA library. Using this hand-made microarray we determined gene expression in various biological systems. To determine tissue specific genes, we compared Nine genes were highly-expressed in adult mouse brain compared to kidney, liver, and skeletal muscle. Tissue distribution analysis using DNA microarray extracted 9 genes that were predominantly expressed in the brain. A database search showed that five of the 9 genes, MBP, SC1, HiAT3, S100 protein-beta, and SNAP25, were previously known to be expressed at high level in the brain and in the nervous system. One gene was highly sequence similar to rat S-Rex-s/human NSP-C, suggesting that the gene is a mouse homologue. The remaining three genes did not match to known genes in the GenBank/EMBL database, indicating that these are novel genes highly-expressed in the brain. Our DNA microarray was also used to detect differentiation specific genes, hormone dependent genes, and transcription-factor-induced genes. We conclude that DNA microarray is an excellent tool for identifying differentially expressed genes.

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Promoter Prediction using Genetic Algorithm (유전자 알고리즘을 이용한 Promoter 예측)

  • 오민경;김창훈;김기봉;공은배;김승목
    • Proceedings of the Korean Information Science Society Conference
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    • 1999.10b
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    • pp.12-14
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    • 1999
  • Promoter는 transcript start site 앞부분에 위치하여 RNA polymerase가 높은 친화성을 보이며 바인당하는 DNA상의 특별한 부위로서 여기서부터 DNA transcription이 시작된다. function이나 tissue-specific gene들의 그룹별로 그 promoter들의 특이한 패턴들의 조합을 발견함으로써 Specific한 transcription을 조절하는 것으로 알려져 있어 promoter로 인한 그 gene의 정보를 어느 정도 알 수가 있다. 사람의 housekeeping gene promoter들을 EPD(eukaryotic promoter database)와 EMBL nucleic acid sequence database로부터 수집하여 이것들 간에 의미 있게 나타나는 모든 패턴들을 optimization algorithm으로 알려진 genetic algorithm을 이용해서 찾아보았다.

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PRaDA : Web-based analyzer for Pathway Relation and Disease Associated SNP (웹 기반 단일염기다형성 연관 패스웨이 분석 도구)

  • Yu, Kijin;Park, Soo Ho;Ryu, Keun Ho
    • Journal of Digital Contents Society
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    • v.19 no.9
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    • pp.1795-1801
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    • 2018
  • Genome-Wide Association Study (GWAS) have been used to identify susceptibility genes for complex human diseases and many recent studies succeed to report common genetic factors for various diseases. Unfortunately, it is hard to understand all biological functions and mechanisms around the complex disease with GWAS only although the number of known associated genes with diseases is increased drastically because GWAS is a single locus based approach while not a gene but numerous factors may affect a disease associated pathways. PRaDA generates a combined report with genes, pathways and Gene Ontology (GO) using single nucleotide polymorphism (SNP) analysis output. The PRaDA reports not only directly associated pathways but also functionally related ones for identifying accumulated effects of low p-value SNPs. Through integrated information including indirect functional effects, user could have insights of overall disease mechanisms and markers.