• 생명과학회지
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• 제29권2호
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• pp.181-190
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• 2019

시스템 약리학적 분석을 통해 대회향(Anisi Stellati Fructus)의 활성성분 스크리닝, 표적유전자 확보 및 관련 질병과의 네트워크를 구축한 후 대회향의 항균작용을 중점적으로 분석하였다. Traditional Chinese Medicine Systems Pharmacology (TCMSP) Database 와 Analysis Platform을 통해 대회향의 잠재적 활성성분 49개를 확보하였으며, 그 중 설정한 조건에 부합하는 9개 활성성분을 스크리닝 하였다. TCMSP Database는 활성성분의 약물 동태학적 특성 및 약물-표적-질병 간의 관련성을 네트워크 수준에서 파악할 수 있는 획기적인 in silico적 접근을 가능하게 해준다. 활성성분과 반응하는 201개의 유전자 정보를 UniProt database를 통해 확인하고, 취합한 유전자들이 관여하는 348개의 생물학적 과정을 David 6.8 Gene Functional Classification Tool에서 확보하였다. Chemokine ligand 2, Interleukin-10, Interleukin-6, Tumor Necrosis Factor를 포함한 총 47개의 유전자가 항균작용에 관여하였고 이들을 표적으로 하는 luteolin, kaempferol, quercetin 등이 대표적 항균 관련 활성성분이었다. 이와 같이 확보된 데이터는 연구 재료 선정에 정확성과 시간, 노력, 비용 절감의 효과를 제공함과 더불어 추후 실험적 증명으로 이어져 감염병의 예방과 치료 전략에 과학적인 근거를 제시할 수 있을 것이다.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2003년도 제2차 연례학술대회 발표논문집
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• pp.164-169
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• 2003

In this paper, we propose the integrated Bayesian network framework to reconstruct genetic regulatory networks from genome expression data. The proposed model overcomes the dimensionality problem of multivariate analysis by building coherent sub-networks from confined gene clusters and combining these networks via intermediary points. Gene Shaving algorithm is used to cluster genes that share a common function or co-regulation. Retrieved clusters incorporate prior biological knowledge such as Gene Ontology, pathway, and protein protein interaction information for extracting other related genes. With these extended gene list, system builds genetic sub-networks using Bayesian network with MDL score and Sparse Candidate algorithm. Identifying functional modules of genes is done by not only microarray data itself but also well-proved biological knowledge. This integrated approach can improve there liability of a network in that false relations due to the lack of data can be reduced. Another advantage is the decreased computational complexity by constrained gene sets. To evaluate the proposed system, S. Cerevisiae cell cycle data [1] is applied. The result analysis presents new hypotheses about novel genetic interactions as well as typical relationships known by previous researches [2].

• 한국가금학회:학술대회논문집
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• 한국가금학회 2005년도 제22차 정기총회 및 학술발표회
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• pp.53-59
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• 2005

본 연구에서는 닭의 정소 및 정자에 대한 기능 유전체 연구를 위한 자원을 확보할 수 있도록 정소 특이적유전자로 예상되는 후보 염기서열을 분석하였다. TIGR Gallus gallus Gene Index 상의 데이터베이스에서 닭의 정소에서만 나타나는 것으로 공개된 EST 염기서열을 검색하여 나온 총 292개의 서열을 선택하였으며, 이와 같이 선별된 서열들에 대하여 닭의 정소와 난소를 포함한 다양한 조직에서 전사체의 발현을 검증하였다. 결과에서, 총 292개의 염기서열 중 110개가 정소 특이적인 발현을 나타내었다. Tentative consensus sequence (TC) 상에서 집합된 EST의 수와 정소 특이적으로 발현하는 TCs의 수 사이의 상관관계는 발견되지 않았다. Gene Ontology 데이터베이스 용어를 이용하여 분류한 결과에서는 정소특이적인 TC는 닭의 전체 TC를 분류한 것과 비교하면 catalytic activity (Molecular Functionbranch)의 카테고리에 많은 수의 TC가 포함된 것으로 나타났다. 본 연구의 결과는 닭의 정소 특이적 유전자에 대한 연구와 그 기능 분석을 보다 더욱 촉진시킬 수 있을 것이다.

• Molecules and Cells
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• 제21권2호
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• pp.269-275
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• 2006

A recent report of the Korean Intellectual Property Office(KIPO) showed that the number of biological sequence-based patents is rapidly increasing in Korea. We present biological features of Korean patented sequences though bioinformatic analysis. The analysis is divided into two steps. The first is an annotation step in which the patented sequences were annotated with the Reference Sequence (RefSeq) database. The second is an association step in which the patented sequences were linked to genes, diseases, pathway, and biological functions. We used Entrez Gene, Online Mendelian Inheritance in Man (OMIM), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Ontology (GO) databases. Through the association analysis, we found that nearly 2.6% of human genes were associated with Korean patenting, compared to 20% of human genes in the U.S. patent. The association between the biological functions and the patented sequences indicated that genes whose products act as hormones on defense responses in the extra-cellular environments were the most highly targeted for patenting. The analysis data are available at http://www.patome.net

• Genomics & Informatics
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• 제18권3호
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• pp.26.1-26.6
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• 2020

Single-cell RNA sequencing (scRNA-seq) has been widely applied to provide insights into the cell-by-cell expression difference in a given bulk sample. Accordingly, numerous analysis methods have been developed. As it involves simultaneous analyses of many cell and genes, efficiency of the methods is crucial. The conventional cell type annotation method is laborious and subjective. Here we propose a semi-automatic method that calculates a normalized score for each cell type based on user-supplied cell type-specific marker gene list. The method was applied to a publicly available scRNA-seq data of mouse cardiac non-myocyte cell pool. Annotating the 35 t-stochastic neighbor embedding clusters into 12 cell types was straightforward, and its accuracy was evaluated by constructing co-expression network for each cell type. Gene Ontology analysis was congruent with the annotated cell type and the corollary regulatory network analysis showed upstream transcription factors that have well supported literature evidences. The source code is available as an R script upon request.

• Journal of Microbiology and Biotechnology
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• 제32권3호
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• pp.365-377
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• 2022

Mammalian target of rapamycin (mTOR) is a serine-threonine kinase member of the cellular phosphatidylinositol 3-kinase (PI3K) pathway, which is involved in multiple biological functions by transcriptional and translational control. mTOR is a downstream mediator in the PI3K/Akt signaling pathway and plays a critical role in cell survival. In cancer, this pathway can be activated by membrane receptors, including the HER (or ErbB) family of growth factor receptors, the insulin-like growth factor receptor, and the estrogen receptor. In the present work, we congregated an electronic network of mTORC1 built on an assembly of data using natural language processing, consisting of 470 edges (activations/interactions and/or inhibitions) and 206 nodes representing genes/proteins, using the Cytoscape 3.6.0 editor and its plugins for analysis. The experimental design included the extraction of gene expression data related to five distinct types of cancers, namely, pancreatic ductal adenocarcinoma, hepatic cirrhosis, cervical cancer, glioblastoma, and anaplastic thyroid cancer from Gene Expression Omnibus (NCBI GEO) followed by pre-processing and normalization of the data using R & Bioconductor. ExprEssence plugin was used for network condensation to identify differentially expressed genes across the gene expression samples. Gene Ontology (GO) analysis was performed to find out the over-represented GO terms in the network. In addition, pathway enrichment and functional module analysis of the protein-protein interaction (PPI) network were also conducted. Our results indicated NOTCH1, NOTCH3, FLCN, SOD1, SOD2, NF1, and TLR4 as upregulated proteins in different cancer types highlighting their role in cancer progression. The MCODE analysis identified gene clusters for each cancer type with MYC, PCNA, PARP1, IDH1, FGF10, PTEN, and CCND1 as hub genes with high connectivity. MYC for cervical cancer, IDH1 for hepatic cirrhosis, MGMT for glioblastoma and CCND1 for anaplastic thyroid cancer were identified as genes with prognostic importance using survival analysis.

• Interdisciplinary Bio Central
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• 제3권2호
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• pp.7.1-7.6
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• 2011

Background: Published manuscripts are the main source of biological knowledge. Since the manual examination is almost impossible due to the huge volume of literature data (approximately 19 million abstracts in PubMed), intelligent text mining systems are of great utility for knowledge discovery. However, most of current text mining tools have limited applicability because of i) providing abstract-based search rather than sentence-based search, ii) improper use or lack of ontology terms, iii) the design to be used for specific subjects, or iv) slow response time that hampers web services and real time applications. Results: We introduce an advanced text mining system called PubMine that supports intelligent knowledge discovery based on diverse bio-ontologies. PubMine improves query accuracy and flexibility with advanced search capabilities of fuzzy search, wildcard search, proximity search, range search, and the Boolean combinations. Furthermore, PubMine allows users to extract multi-dimensional relationships between genes, diseases, and chemical compounds by using OLAP (On-Line Analytical Processing) techniques. The HUGO gene symbols and the MeSH ontology for diseases, chemical compounds, and anatomy have been included in the current version of PubMine, which is freely available at http://pubmine.kobic.re.kr. Conclusions: PubMine is a unique bio-text mining system that provides flexible searches and analysis of biological entity relationships. We believe that PubMine would serve as a key bioinformatics utility due to its rapid response to enable web services for community and to the flexibility to accommodate general ontology.

• Biomolecules & Therapeutics
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• 제22권2호
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• pp.143-148
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• 2014

Marfan syndrome (MFS) is a dominantly inherited connective tissue disorder caused by mutations in the gene encoding fibrillin-1 (FBN1) and is characterized by aortic dilatation and dissection, which is the primary cause of death in untreated MFS patients. However, disease progression-associated changes in gene expression in the aortic lesions of MFS patients remained unknown. Using a mouse model of MFS, FBN1 hypomorphic mouse (mgR/mgR), we characterized the aortic gene expression profiles during the progression of the MFS. Homozygous mgR mice exhibited MFS-like phenotypic features, such as fragmentation of elastic fibers throughout the vessel wall and were graded into mgR1-4 based on the pathological severity in aortic walls. Comparative gene expression profiling of WT and four mgR mice using microarrays revealed that the changes in the transcriptome were a direct reflection of the severity of aortic pathological features. Gene ontology analysis showed that genes related to oxidation/reduction, myofibril assembly, cytoskeleton organization, and cell adhesion were differentially expressed in the mgR mice. Further analysis of differentially expressed genes identified several candidate genes whose known roles were suggestive of their involvement in the progressive destruction of aorta during MFS. This study is the first genome-wide analysis of the aortic gene expression profiles associated with the progression of MFS. Our findings provide valuable information regarding the molecular pathogenesis during MFS progression and contribute to the development of new biomarkers as well as improved therapeutic strategies.

• Genomics & Informatics
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• 제20권3호
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• pp.26.1-26.19
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• 2022

Diabetes and its related complications are associated with long term damage and failure of various organ systems. The microvascular complications of diabetes considered in this study are diabetic retinopathy, diabetic neuropathy, and diabetic nephropathy. The aim is to identify the weighted co-expressed and differentially expressed genes (DEGs), major pathways, and their miRNA, transcription factors (TFs) and drugs interacting in all the three conditions. The primary goal is to identify vital DEGs in all the three conditions. The overlapped five genes (AKT1, NFKB1, MAPK3, PDPK1, and TNF) from the DEGs and the co-expressed genes were defined as key genes, which differentially expressed in all the three cases. Then the protein-protein interaction network and gene set linkage analysis (GSLA) of key genes was performed. GSLA, gene ontology, and pathway enrichment analysis of the key genes elucidates nine major pathways in diabetes. Subsequently, we constructed the miRNA-gene and transcription factor-gene regulatory network of the five gene of interest in the nine major pathways were studied. hsa-mir-34a-5p, a major miRNA that interacted with all the five genes. RELA, FOXO3, PDX1, and SREBF1 were the TFs interacting with the major five gene of interest. Finally, drug-gene interaction network elucidates five potential drugs to treat the genes of interest. This research reveals biomarker genes, miRNA, TFs, and therapeutic drugs in the key signaling pathways, which may help us, understand the processes of all three secondary microvascular problems and aid in disease detection and management.

• 한국버섯학회지
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• 제20권1호
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• pp.7-12
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• 2022

The ascomycete fungus Cordyceps militaris infects lepidopteran insect pupae, forming characteristic fruiting bodies called "Dong Chung Ha Cho" in Korean. They have been used as medicines owing to their anti-allergic, anti-inflammatory, and immune-enhancing effects. This fungus can be grown on the geminated soybeans Rhynchosia nulubilis, which also contains several novel isoflavones. We performed a comparative transcriptome analysis to determine core gene sets or pathways contributing to biologically active products such as isoflavone. Initially, we sequenced 2-week-old fungal cultures on different soybean agar media, where different amounts of water agar were implemented to show different surface topology. We selected 830 upregulated and 188 downregulated genes by comparing linear models of the samples (two-fold change threshold). Gene ontology analysis identified that the "IMP biosynthesis" term was significantly found in the upregulated gene sets. The pathway is involved in the synthesis of cordycepin, the reference chemical for C. militaris. This finding in the transcriptome data is consistent with the previous observation: increased cordycepin concentrations in the C. militaris cultured on germinated soybean.