• Genomics & Informatics
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• v.1 no.2
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• pp.75-79
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• 2003

Every protein can be characterized by either a distinct motif or a combination of motifs. Nevertheless, little is known about the relationships among (more than two) the motifs. Some of the proteins in the world are share motifs for evolutional or other biological benefits - they can save energy, time and resource for controlling and managing a variety of proteins. In some cases of motifs, the tendency is quite common and they can act the 'hub' motif of a network of the motif associations. The hubs are structurally and functionally important in themselves and also important in disease-related mutations. They will be highly resistant mutation to conserve their functions. But, in case of the a rare mutation, mutations on the position of hub can more easily cause fatal diseases.

• Genomics & Informatics
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• v.13 no.3
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• pp.76-80
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• 2015

Type 2 diabetes mellitus is a complex metabolic disorder associated with multiple genetic, developmental and environmental factors. The recent advances in gene expression microarray technologies as well as network-based analysis methodologies provide groundbreaking opportunities to study type 2 diabetes mellitus. In the present study, we used previously published gene expression microarray datasets of human skeletal muscle samples collected from 20 insulin sensitive individuals before and after insulin treatment in order to construct insulin-mediated regulatory network. Based on a motif discovery method implemented by iRegulon, a Cytoscape app, we identified 25 candidate regulons, motifs of which were enriched among the promoters of 478 up-regulated genes and 82 down-regulated genes. We then looked for a hierarchical network of the candidate regulators, in such a way that the conditional combination of their expression changes may explain those of their target genes. Using Genomica, a software tool for regulatory network construction, we obtained a hierarchical network of eight regulons that were used to map insulin downstream signaling network. Taken together, the results illustrate the benefits of combining completely different methods such as motif-based regulatory factor discovery and expression level-based construction of regulatory network of their target genes in understanding insulin induced biological processes and signaling pathways.

• Proceedings of the Korean Magnetic Resonance Society Conference
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• 2000.08a
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• pp.23-24
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• 2000

• IMMUNE NETWORK
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• v.16 no.4
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• pp.249-255
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• 2016

Exogenous nucleic acids induce an innate immune response in mammalian host cells through activation of the retinoic acid-inducible gene I (RIG-I). We evaluated RIG-I protein for RNA binding and ATPase stimulation with RNA ligands to investigate the correlation with the extent of immune response through RIG-I activation in cells. RIG-I protein favored blunt-ended, double-stranded RNA (dsRNA) ligands over sticky-ended dsRNA. Moreover, the presence of the 5'-triphosphate (5'-ppp) moiety in dsRNA further enhanced binding affinity to RIG-I. Two structural motifs in RNA, blunt ends in dsRNA and 5'-ppp, stimulated the ATP hydrolysis activity of RIG-I. These structural motifs also strongly induced IFN expression as an innate immune response in cells. Therefore, we suggest that IFN induction through RIG-I activation is mainly determined by structural motifs in dsRNA that increase its affinity for RIG-I protein and stimulate ATPase activity in RIG-I.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.594-598
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• 2005

복잡한 유전학적 네트워크 구조와 조직을 해석하여 인터넷 네트워크에서 상호연결 하는 '네트워크 모티프'를 연구한다. 다양하고 복잡한 유전학적 네트워크 구조의 설계 및 원리를 해석한 네트워크 모티프를 패턴으로 규정되어 있는 것들을 유전학적 네트워크에서 정보 네트워크(www)와의 동적으로 수행할 수 있는지 알고리즘을 통해 해석한다. 유전학적 네트워크에서 모티프들이 네트워크의 보편적인 class를 규정할 수 있는지 이론적으로 접근하여 인터넷 네트워크에 응용 및 해석하고 분석한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.8
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• pp.1386-1392
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• 2006

This study is a numerical representative modelling analysis for applying the process that unravels networks between cells in genetics to WWW of informatics. Using the probabilistic graphical model, the insight from the data describing biological networks is used for making a probabilistic function. Rather than a complex network of cells, we reconstruct a simple lower-stage model and show a genetic representation level from the genetic based network logic. We made probabilistic graphical models from genetic data and extends them to genetic representation data in the method of network modelling in informatics.

• KSBB Journal
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• v.21 no.4
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• pp.231-235
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• 2006

This study is a numerical representative modeling analysis for the application of the process that unravels networks between cells in genetics to web of informatics. Using the probabilistic graphical model, the insight from the data describing biological networks is used for making a probabilistic function. Rather than a complex network of cells, we reconstruct a simple lower-stage model and show a genetic representation level from the genetic based network logic. We made probabilistic graphical models from genetic data and extends them to genetic representation data in the method of network modeling in informatics

• Bioinformatics and Biosystems
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• v.2 no.2
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• pp.52-57
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• 2007

The computational discovery of transcription factor binding site is one of the important tools in the genetic and genomic analysis. Rough prediction of gene regulation network and finding possible co-regulated genes are typical applications of the technique. Countless motif-discovery algorithms have been proposed for the past years. However, there is no dominant algorithm yet. Each algorithm does not give enough accuracy without extensive information. In this paper, we explore the possibility of combining multiple algorithms for the one integrated result in order to improve the performance and the convenience of researchers. Moreover, we apply new high order information that is reorganized from the set of basis predictions to the final prediction.

• Journal of the Korean Chemical Society
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• v.63 no.1
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• pp.29-36
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• 2019

A potentially tetradentate Schiff base ligand, 2-((2-((pyridin-2-ylmethylene)amino)ethyl)amino)ethan-1-ol (PMAE), and its cadmium(II) complex, [$Cd(PMAE)I_2$] (1), were prepared and characterized by elemental analysis, FT-IR, Raman, $^1H$ and $^{13}C$ NMR spectroscopies and single-crystal X-ray diffraction. In the crystal structure of 1, the cadmium atom has a slightly distorted square-pyramidal geometry and a $CdN_3I_2$ environment in which the PMAE acts as an $N_3$-donor. In the crystal packing of the complex, the alcohol and amine groups of the coordinated ligands participate in hydrogen bonding with iodide ions and form $R^2{_2}(14)$ and $R^2{_2}(8)$ hydrogen bond motifs, respectively. In addition to the hydrogen bonds, the crystal network is stabilized by ${\pi}-{\pi}$ stacking interactions between pyridine rings. The thermodynamic stability of the isolated ligand and its cadmium complex along with their charge distribution patterns were studied by DFT and NBO analysis.

• IMMUNE NETWORK
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• v.16 no.3
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• pp.176-182
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• 2016

CCR3 is a chemokine receptor that mediates the accumulation of allergic inflammatory cells, including eosinophils and Th2 cells, at inflamed sites. The regulatory sequence of the CCR3 gene, contains two Runt-related transcription factor (RUNX) 1 sites and two PU.1 sites, in addition to a functional GATA site for transactivation of the CCR3 gene. In the present study, we examined the effects of the cis-acting elements of RUNX1 and PU.1 on transcription of the gene in EoL-1 eosinophilic cells and Jurkat T cells, both of which expressed functional surface CCR3 and these two transcription factors. Introduction of RUNX1 siRNA or PU.1 siRNA resulted in a modest decrease in CCR3 reporter activity in both cell types, compared with transfection of GATA-1 siRNA. Cotransfection of the two siRNAs led to inhibition in an additive manner. EMSA analysis showed that RUNX1, in particular, bound to its binding motifs. Mutagenesis analysis revealed that all point mutants lacking RUNX1- and PU.1-binding sites exhibited reduced reporter activities. These results suggest that RUNX1 and PU.1 participate in transcriptional regulation of the CCR3 gene.