• 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

• 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.

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.3
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• pp.168-176
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• 2023

Silicon (Si) has the potential to improve plant growth and stress tolerance. The study aimed to explore Si-involving plant responses and molecular characterization of different Si-responsive genes in alfalfa. In this study, the exogenous supplementation of Si enhanced plant growth, and biomass yield. Si-acquisition in alfalfa root and shoot was higher in Si-supplemented compared to silicon deficient (-Si) plants, implying Si-acquisition has beneficial on alfalfa plants. As a consequence, the quantum efficiency of photosystem II (Fv/Fm) was significantly increased in silicon-sufficient (+Si) plants. The quantitative gene expression analysis exhibited a significant upregulation of the Lsi1, Lsi2, Lsi3, NIP5;1, and NIP6;1 genes in alfalfa roots, while BOR1, BOR4, NIP2, and NIP3 showed no significant variation in their expression. The MEME results further noticed the association of four motifs related to the major intrinsic protein (MIP). The interaction analysis revealed that NIP5;1 and Lsi1 showed a shared gene network with NIP2, BOR1, and BOR4, and Lsi2, Lsi3 and NIP3-1, respectively. These results suggest that members of the major intrinsic proteins (MIPs) family especially Lsi1, Lsi2, Lsi3, NIP5;1, and NIP6;1 genes helped to pass water and other neutral solutes through the cell membrane and those played significant roles in Si uptake and transport in plants. Together, these insights might be useful for alfalfa breeding and genome editing approaches for alfalfa improvement.

• IMMUNE NETWORK
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• v.1 no.1
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• pp.61-69
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• 2001

Background: To determine the molecular structure of type II collagen-specific T-cell receptors associated with rheumatoid arthritis (RA). Methods: We generated CII-specific T-cell lines of 8 RA patients by prolonged in vitro culture with bovine CII (bCII) and the immunogenic peptide (256-270) of human CII. The proliferation response towards CII stimulation was measured from the uptake of 3H-thymidine. Changes in the secretion of Th 1 and Th2 cytokines in the culture supernatent were measured by ELISA. The TCR clonotypes of these T-cells were examined by RT-PCR/SSCP analyses of all 22 $V_{\beta}$ chains. Results: T-cells from patients' tissue exhibited strong proliferation index upon CII stimulation, which was maintained up to 6 months in the culture. The secretion of INF-$\gamma$from these T-cells increased along with the duration of culture time, while the amount of IL-4 production did not show significant changes. The SSCP band patterns of patients' T-cells appear as discrete bands unlike the smeary streak produced from normal samples. Some SSCP bands, each representing selected expansion of a TCR containing certain subtype of $V_{\beta}$ peptides, appeared to be identical in more than one patients. Among these, the expansion of SSCP band representing the $V_{\beta}$ 14 CDR3 region persisted after switching the antigen to the immunogenic human peptide (256-270). Conclusion: CII-reactive T-cells expressing distinct CDR3 motifs are selectively expanded in the peripheral blood and synovial fluid of RA patients, and their persistent proliferation upon CII stimulation, as well as the production Th 1-type cytokines, may play pivotal roles in RA pathogenesis.