• 한국산업정보학회논문지
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• 제12권5호
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• pp.1-13
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• 2007

본 연구에서는 단백질 상호작용 네트워크에서 네트워크 견고성의 핵심노드는 허브노드이지만 연결노드 또한 허브노드와 같이 매우 중요한 역할을 하고 있음을 밝혀냈다. 네트워크 견고성에 가장 큰 영향을 미치는 핵심노드는 차수가 매우 큰 허브이다. 이 연구에서 새로이 제안된 연결노드는 단백질상호 작용 네트워크에서 고밀도로 연결된 모듈들 사이에 위치하여 네트워크 견고성에 중요한 영향을 미치는 노드이다. 실제로 척도 없는 네트워크는 무작위 공격에 매우 강한 반면, 허브노드만을 제거하는 목표 공격에는 매우 취약하다. 기존에 핵심노드로 노드의 연결성을 연구한 방식과 사이 중앙성(centrality)을 기반으로 사이 중앙성(betweenness centrality)이 큰 노드가 전체 네트워크에서 핵심노드임을 연구한 방식이 있다. 그러나 노드의 연결성 즉, 차수와 사이 중앙성은 일정한 비례관계가 있어서 차수가 클수록 사이 중앙성 값이 커지기 때문에 기존의 두 연구는 큰 차이점을 갖지 못한다. 본 연구에서는 단백질 상호작용 네트워크도 척도 없는 네트워크이므로 노드의 차수와 사이 중앙성 간에 비례관계가 형성되지만, 차수가 작은 노드일수록 사이 중앙성 값이 매우 넓게 분포하고 있다는 특징에 착안하여 연결노드를 제안한다. 이 연구에서는 차수가 매우 작지만 사이 중앙성 값이 매우 큰 노드를 연결노드로 간주하여 실제 인터넷 상에서 공개된 생물 네트워크를 대상으로 견고성 분석 실험을 한다. 실험 결과 연결노드들이 생물 네트워크에서 제거되면 허브노드가 제거되는 것보다 더욱 큰 네트워크 분화가 발생하였으며, 이는 연결노드가 네트워크 견고성 측면에서 매우 중요한 요소임을 입증하는 것이다.는 $30^{\circ}C$에서 20분간 안정하였다.다.. 금속산화물반도체 전계효과 트랜지스터를 살펴보면 격자산란이 주로 표면에서 일어나기 때문에 1/f-형 잡음이 표면효과라고 말할 수 있다.이 가수분해되어 생성된 카르복실산 염(sodium carboxylate) 때문인 것으로 판단되었다.산화효과 (in vitro)가 있음이 증명되었으며, 이 항산화활성은 극성이 비교적 큰 화합물들에 의한 것임을 추정할 수 있다. 현재 쇠비름 추출물로부터 항산화활성성분을 분리하기 위한 연구가 진행 중이다.는 exp-onential phase 동안 급격한 균체성장으로 용존산소가 부족하여 NADH balance에 의해 astaxanthin 생합성 경로 중 탈수소화 단계가 저해되기 때문으로 사료되었다. 최종 세포농도는 43.3 g/L, 단위부피당 carotenoids 함량은 149.4 mg/L, astaxanthin 함량은 110.6 mg/L로서 산업적인 생산성이 있는 것으로 나타났다. 이번 연구를 통하여 개발된 변이주 B76 및 이의 대량 발효를 위한 최종조건의 정립은 향후 astaxanthin의 산업적 생산공정에 필요한 기초자료로 이용될 것으로 기대된다.색총말내에 소형의 도형, 소형의 장형 연접소포 및 DENSE CORE VESICLE의 3가지 연접소포를 가지고 있었고 출현빈도수는 촉각엽에서 가장 큰 33%이었다. 제5형 신경연접은 축색종말내에 중등도크기의 원형, 대형의 원형연접소포 및 DENSE CORE VESICLE을 포함하였고 13%의 출현빈도수로 관찰되었다. 배추횐나비의 촉각에 있는 지각신경세포가 뇌의 촉각엽으로 뻗어 들어가 위의 5가지 신경연접중 어느

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2014년도 춘계 종합학술대회 논문집
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• pp.55-56
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• 2014

• 한국당과학회:학술대회논문집
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• 한국당과학회 2006년도 제1회 연례학술대회
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• pp.48-48
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• 2006

• 한국정보과학회논문지:시스템및이론
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• 제34권10호
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• pp.474-492
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• 2007

단백질 상호작용 네트워크는 생체 내에서 특정 역할을 담당하는 패스웨이나 복합체와 같은 중요한 의미의 많은 기능 모듈들을 포함하고 있다. 본 논문에서는 이 기능 모듈들과 정합될 수 있는 개념 모듈을 정의하고 이를 기반으로 원하는 기능 모듈들을 개념적으로 표현하고 효율적으로 탐색할 수 있는 새로운 방법을 제안한다. 개념 모듈은 트리플들과 이들 사이의 연산자로 이루어진 표현 규칙에 의해 정의 되며 탐색하고자 하는 기능 모듈들의 구조를 개념적으로 표현한다. 이 표현 규칙에서의 트리플은 한 기능 모듈을 구성하는 단백질들 사이의 구체적인 상호작용 관계를, 연산자는 트리플들 사이의 구조적인 연관 관계를 각각 개념적으로 정의한다. 또한, 사용자는 사전에 표현 규칙에 의해 잘 정의된 개념들을 조합하여 새로운 의미의 복합 개념 모듈을 정의할 수도 있다. 복합 개념 모듈은 복잡한 기능 모듈들의 개념적 구조를 보다 정교하게 표현할 수 있기 때문에, 사용자 탐색 질의의 의미적 표현력을 획기적으로 높일 수 있다. 정의된 규칙들은 XML로 관리될 수 있어 다른 종류의 단백질 상호작용 네트워크에서 사용자가 유사한 모듈들을 탐색하기 위해 쉽게 적용 가능하다. 본 논문에서는 또한, 구조적으로 복잡한 규칙들을 직관적으로 표현하고 효율적으로 탐색하기 위한 시각화된 질의 환경도 구현하였다.

• Journal of Biosystems Engineering
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• 제43권2호
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• pp.148-159
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• 2018

Purpose: Unmanned air vehicle (UAV) remote sensing was applied to test various vegetation indices and make prediction models of protein content of rice for monitoring grain quality and proper management practice. Methods: Image acquisition was carried out by using NIR (Green, Red, NIR), RGB and RE (Blue, Green, Red-edge) camera mounted on UAV. Sampling was done synchronously at the geo-referenced points and GPS locations were recorded. Paddy samples were air-dried to 15% moisture content, and then dehulled and milled to 92% milling yield and measured the protein content by near-infrared spectroscopy. Results: Artificial neural network showed the better performance with $R^2$ (coefficient of determination) of 0.740, NSE (Nash-Sutcliffe model efficiency coefficient) of 0.733 and RMSE (root mean square error) of 0.187% considering all 54 samples than the models developed by PR (polynomial regression), SLR (simple linear regression), and PLSR (partial least square regression). PLSR calibration models showed almost similar result with PR as 0.663 ($R^2$) and 0.169% (RMSE) for cloud-free samples and 0.491 ($R^2$) and 0.217% (RMSE) for cloud-shadowed samples. However, the validation models performed poorly. This study revealed that there is a highly significant correlation between NDVI (normalized difference vegetation index) and protein content in rice. For the cloud-free samples, the SLR models showed $R^2=0.553$ and RMSE = 0.210%, and for cloud-shadowed samples showed 0.479 as $R^2$ and 0.225% as RMSE respectively. Conclusion: There is a significant correlation between spectral bands and grain protein content. Artificial neural networks have the strong advantages to fit the nonlinear problem when a sigmoid activation function is used in the hidden layer. Quantitatively, the neural network model obtained a higher precision result with a mean absolute relative error (MARE) of 2.18% and root mean square error (RMSE) of 0.187%.

• 한국미생물학회:학술대회논문집
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• 한국미생물학회 2004년도 International Meeting of the Microbiological Society of Korea
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• pp.65-67
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• 2004

O-GlcNAcylation of p53 has been already identified and reported, but the function of O-GlcNAc on p53 has not been studied well. In this report, the general function of O-GlcNAc modification on p53 has been investigated using mouse fibroblast cell, L929. When streptozotocin (STZ), a non-competitive O-GlcNAcase inhibitor was treated to L929, O-GlcNAc modification level was dramatically increased on nucleocytoplasmic proteins, including p53. Because it has been already reported that $TNF\alpha$ induced the production of p53 in L929, $TNF\alpha$ was treated to obtain more p53. Approximately two times more amount of p53 was found from the cells treated STZ and $TNF\alpha$ simultaneously compared to the cell treated $TNF\alpha$ alone. The p53 increment in the presence of STZ was not caused by the induction of p53 gene expression. When new production of p53 induced by the $TNF\alpha$ was inhibited by the treatment of cycloheximide, O-GlcNAc modification decreased and phosphorylation increased on pre-existing p53 after $TNF\alpha$ treatment. But in the presence of STZ and $TNF\alpha$ at the same time, more O-GlcNAcylation occurred on p53, The level of ubiquitination on p53 was also reduced in the presence of STZ. Approximately three times less amount of Mdm2 bound to this hyperglycosylated p53. From this result it might be concluded that treatment of STZ to inhibit O-GlcNAcase increased O-GlcNAc modification level on p53 and the increment of O-GlcNAc modification stabilized p53 from ubiquitin proteolysis system.

• 턱관절균형의학회지
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• 제10권1호
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• pp.12-20
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• 2020

Objectives: Tourette syndrome (TS) is a disease that occurs evenly in many social classes. Despite the long experience of drug treatment, the preference is low due to various side effects. The aim of this study was to discover herbal medicine resources through network pharmacology analysis predicted to be useful for Tourette syndrome. Methods: We used Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) to identify herbal medicines that can be used for TS by using network pharmacology research methods and to predict the mechanism of action. After evaluating compounds of each identified herb, molecular target proteins and mechanisms of action were analyzed, focusing on compounds that are likely to exhibit clinical activity in consideration of the pharmacokinetic parameters of these individual compounds. Results: Fifty nine ingredients such as atropine, veraguensin, and nuciferin among the compounds contained in 48 types of medicinal herbs such as Daturae Flos (洋金花), Salviae Radix (丹参), and Nelumbinis Plumula (蓮子心) act on the D(2) dopamine receptor, which is a protein involved in the development of TS. It has been found that atropine, veraguensin, and nuciferin are highly likely to exhibit activity by acting on the G protein-coupled receptor signaling pathway. Conclusions: It can be used in conjunction with non-invasive treatment means such as FCST Yinyang Balancing Appliance with herbal therapy to bring about a significant therapeutic effect, and it will be possible to develop a treatment that can replace drug therapy used in Western medicine.

• Journal of Korean Neurosurgical Society
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• 제65권5호
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• pp.697-709
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• 2022

Objective : The present study aimed to identify the function of ischemic stroke (IS) patients' peripheral blood and its role in IS, explore the pathogenesis, and provide direction for clinical research progress by comprehensive bioinformatics analysis. Methods : Two datasets, including GSE58294 and GSE22255, were downloaded from Gene Expression Omnibus database. GEO2R was utilized to obtain differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed using the database annotation, visualization and integrated discovery database. The protein-protein interaction (PPI) network of DEGs was constructed by search tool of searching interactive gene and visualized by Cytoscape software, and then the Hub gene was identified by degree analysis. The microRNA (miRNA) and miRNA target genes closely related to the onset of stroke were obtained through the miRNA gene regulatory network. Results : In total, 36 DEGs, containing 27 up-regulated and nine down-regulated DEGs, were identified. GO functional analysis showed that these DEGs were involved in regulation of apoptotic process, cytoplasm, protein binding and other biological processes. KEGG enrichment analysis showed that these DEGs mediated signaling pathways, including human T-cell lymphotropic virus (HTLV)-I infection and microRNAs in cancer. The results of PPI network and cytohubba showed that there was a relationship between DEGs, and five hub genes related to stroke were obtained : SOCS3, KRAS, PTGS2, EGR1, and DUSP1. Combined with the visualization of DEG-miRNAs, hsa-mir-16-5p, hsa-mir-181a-5p and hsa-mir-124-3p were predicted to be the key miRNAs in stroke, and three miRNAs were related to hub gene. Conclusion : Thirty-six DEGs, five Hub genes, and three miRNA were obtained from bioinformatics analysis of IS microarray data, which might provide potential targets for diagnosis and treatment of IS.

• Asian Pacific Journal of Cancer Prevention
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• 제14권6호
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• pp.3669-3676
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• 2013

Faithful transmission of genetic information depends on accurate chromosome segregation as cells exit from mitosis, and errors in chromosomal segregation are catastrophic and may lead to aneuploidy which is the hallmark of cancer. In eukaryotes, an elaborate molecular control system ensures proper orchestration of events at mitotic exit. Phosphorylation of specific tyrosyl residues is a major control mechanism for cellular proliferation and the activities of protein tyrosine kinases and phosphatases must be integrated. Although mitotic kinases are well characterized, phosphatases involved in mitosis remain largely elusive. Here we identify a novel variant of mouse protein tyrosine phosphatase containing domain 1 (Ptpcd1), that we named Ptpcd2. Ptpcd1 is a Cdc14 related centrosomal phosphatase. Our newly identified Ptpcd2 shared a significant homology to yeast Cdc14p (34.1%) and other Cdc14 family of phosphatases. By subcellular fractionation Ptpcd2 was found to be enriched in the cytoplasm and nuclear pellets with catalytic phosphatase activity. By means of immunofluorescence, Ptpcd2 was spatiotemporally regulated in a cell cycle dependent manner with cytoplasmic abundance during mitosis, followed by nuclear localization during interphase. Overexpression of Ptpcd2 induced mitotic exit with decreased levels of some mitotic markers. Moreover, Ptpcd2 failed to colocalize with the centrosomal marker ${\gamma}$-tubulin, suggesting it as a non-centrosomal protein. Taken together, Ptpcd2 phosphatase appears a non-centrosomal variant of Ptpcd1 with probable mitotic functions. The identification of this new phosphatase suggests the existence of an interacting phosphatase network that controls mammalian mitosis and provides new drug targets for anticancer modalities.

• Journal of Microbiology and Biotechnology
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• 제22권8호
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• pp.1054-1058
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• 2012

In order to predict biologically significant attributes such as function from protein sequences, searching against large databases for homologous proteins is a common practice. In particular, BLAST and HMMER are widely used in a variety of biological fields. However, sequence-homologous proteins determined by BLAST and proteins having the same domains predicted by HMMER are not always functionally equivalent, even though their sequences are aligning with high similarity. Thus, accurate assignment of functionally equivalent proteins from aligned sequences remains a challenge in bioinformatics. We have developed the FEP-BH algorithm to predict functionally equivalent proteins from protein-protein pairs identified by BLAST and from protein-domain pairs predicted by HMMER. When examined against domain classes of the Pfam-A seed database, FEP-BH showed 71.53% accuracy, whereas BLAST and HMMER were 57.72% and 36.62%, respectively. We expect that the FEP-BH algorithm will be effective in predicting functionally equivalent proteins from BLAST and HMMER outputs and will also suit biologists who want to search out functionally equivalent proteins from among sequence-homologous proteins.