• Proceedings of the Microbiological Society of Korea Conference
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• 2002.10a
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• pp.135-139
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• 2002

Yeast cells respond to condition of amino acid starvation by synthesizing GCN4, a typical eukaryotic transcriptional activator, which regulates the expression of many amino acids biosynthetic genes. By introducing point mutations in the DNA binding domain of GCN4, mutants with normal DNA binding activity but defective in transcriptional activity were isolated to identify unknown proteins that could suppress the mutant phenotype under an amino acid depletion condition. As a result, SSB(Stress-Seventy B) subfamily proteins were identified as suppressors of mutant GCN4. SSB proteins were known as a member of yeast hsp70 family that probably aids passage of nascent chain through ribosomes. Among them, the mechanism of suppression by SSB2 on the defective GCN4 mutant strains is under investigation. Gcn4p directly interacts with Ssb2p through the basic DNA binding domain of GCN4. It suggests the possibility that physical interaction might induce the transcriptional activation of Gcn4p.

• Microbiology and Biotechnology Letters
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• v.19 no.1
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• pp.37-44
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• 1991

- I aimed to isolate trans-acting factors involved in the basal expression level of eukaryotic genes. One of the yeast histidine biosynthetic gene, HIS5 was taken as a model for this study. HIS5 gene has a substantial basal level in amino acid rich medium and is derepressed if starved for any single amino acid. The derepression is mediated by cis-acting DNA sequences 5'-TGACTC-3' found in 5' non-transcribed region of the gene and trans-acting factors including GCN4 as positive factor and its negative factor GCDI 7, and GCNZ as a negative factor of GCD17. I first investigated the role of these trans-acting factors in HIS5 basal expression level by using HIS5-pH05 fusion in which expression of pH05 gene encoding inorganic phosphate-repressible acid phosphatase (APase) is regulated by HIS5 promoter. Strain with gcn2 or gcn4 mutation showed 3 to 4 fold lower APase activity than wild type. The level of APase activity was similar in gcn2 and gcn4 mutants. Trans-acting factors involved in basal level were identified by isolating 14 mutants showing increased expression of HISSPH05 fusion from gcn4 background. All the mutants carry a single nuclear recessive mutation and fall into four complementation groups, designated as bell (basal expression level), be12, be23 and be14.

• Molecules and Cells
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• v.24 no.2
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• pp.194-199
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• 2007

GCN4 is a typical eukaryotic transcriptional activator that is implicated in the expression of many genes involved in amino acids and purine biosyntheses under stress conditions. It is degraded by 26S proteasomes following ubiquitination. However, the immediate receptor for ubiquitinated Gcn4p has not yet been identified. We investigated whether ubiquitinated Gcn4p binds directly to Rpn10p as the ubiquitinated substrate receptor of the 26S proteasome. We found that the level of Gcn4p increased in cells deleted for Rpn10p but not in cells deleted for RAD23 and DSK2, the other ubiquitinated substrate receptors and, unlike Rpn10p, neither of these proteins recognized ubiquitinated Gcn4p. These results suggest that Rpn10p is the receptor that binds the polyubiquitin chain during ubiquitin-dependent proteolysis of Gcn4p.

• Journal of Microbiology
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• v.37 no.3
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• pp.154-158
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• 1999

The arginine residue at position 243 (Arg 243) of the yeast transcription factor, Gcn4p, is invariably conserved among bZIP transcription factors. Using site-directed oligonucleotide saturation mutagenesis involving two-step polymerase chain reaction (PCR) amplification, random mutations were successfully introduced at the codon of 243 in the basic domain of Gcn4p. This mutant library was transformed ito Gcn4p defective yeast strain and selected for the transcriptionally active colonies. All colonies which were transcriptionally active had arginines in the codon 243. In this study, the strand preference by Taq polymerase during mutagenesis was also tested. Oligonucleotides were specially designed to test whether or not the polymerase was preferred using the strand as a template. A population of randomly mutated products were cloned into an appropriate vector and characterized by DNA sequencing analysis. Saturation mutagenesis which was performed efficiently by this method revealed a strong bias in terms of strand preference of Taq polymerase by an approximate ratio of 3 to 1 in this study.

• Journal of Microbiology and Biotechnology
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• v.9 no.1
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• pp.122-125
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• 1999

Gcn4p, a transcriptional activator protein of the yeast, Sacchromyces cerevisiae, binds to the specific sequence in the promoters of many amino acid biosynthetic genes for general control. The serine residue (Ser 242) of Gcn4p directly contacts the DNA. Here, for inspecting the DNA binding properties and the level of transcriptional activation of Gcn4p, we introduced a polymerase chain reaction (PCR) site-directed saturation mutation library into the Ser 242 site using 2 outside primers and 2 oligonucleotides with its codons fully degenerated. The sequencing analysis of 146 samples revealed the even nucleotide distribution within the experimental error showing 23, 26, 25, and 26％ frequency of U, C, A, and G bases, respectively. This method turned out to be a simple, fast, and economical method for constructing a library of all 20 amino acids at specific codon.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.652-655
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• 2023

우리나라에서는 지난 10년간 매년 4만 건 내외의 화재가 발생하여 많은 인명 피해와 경제적 손실이 발생하고 있다. 화재가 발생했을 때는 화재를 신속히 진압하여 인명 피해와 경제적 손실을 최소화하여야 한다. 또한, 화재 사고를 예방하기 위해 화재의 발화 원인이 무엇인지 알아내야 한다. 기존의 화재 경보 시스템에서는 온도, 연기, 불꽃 센서 등으로 화재를 감지하였으나 오경보나 화재를 인식하지 못하는 문제, 화재 원인을 구분하지 못하는 문제 등이 있었다. 또한, 사람이 화재 발생을 인지하기까지 시간이 많이 소요될 수 있고 부재로 인해 화재 상황인식이 늦어질 수도 있는 문제가 있었다. 이러한 문제를 해결하기 위해 본 논문에서는 GCN(Graph Convolutional Network) 모델을 이용하여 화재 상황에서의 복합 센서 상황을 학습해서 실제 화재 사고가 발생했을 때 화재의 원인을 구분할 수 있는 모델을 제안한다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.314-322
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• 2021

Skeleton-based action recognition has attracted considerable attention in human action recognition. Recent methods for skeleton-based action recognition employ spatiotemporal graph convolutional networks (GCNs) and have remarkable performance. However, most of them have heavy computational complexity for robust action recognition. To solve this problem, we propose a shuffle graph convolutional network (SGCN) which is a lightweight graph convolutional network using pointwise group convolution rather than pointwise convolution to reduce computational cost. Our SGCN is composed of spatial and temporal GCN. The spatial shuffle GCN contains pointwise group convolution and part shuffle module which enhances local and global information between correlated joints. In addition, the temporal shuffle GCN contains depthwise convolution to maintain a large receptive field. Our model achieves comparable performance with lowest computational cost and exceeds the performance of baseline at 0.3% and 1.2% on NTU RGB+D and NTU RGB+D 120 datasets, respectively.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.88-97
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• 2023

Traffic flow prediction is of great significance in urban planning and traffic management. As the complexity of urban traffic increases, existing prediction methods still face challenges, especially for the fusion of spatiotemporal information and the capture of long-term dependencies. This study aims to use the fusion model of graph neural network to solve the spatio-temporal information fusion problem in traffic flow prediction. We propose a new deep learning model Spatio-Temporal Information Fusion using Graph Neural Networks (STFGNN). We use GCN module, TCN module and LSTM module alternately to carry out spatiotemporal information fusion. GCN and multi-core TCN capture the temporal and spatial dependencies of traffic flow respectively, and LSTM connects multiple fusion modules to carry out spatiotemporal information fusion. In the experimental evaluation of real traffic flow data, STFGNN showed better performance than other models.

• Molecules and Cells
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• v.38 no.12
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• pp.1037-1043
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• 2015

The TAZ activator 2-butyl-5-methyl-6-(pyridine-3-yl)-3-[2'-(1H-tetrazole-5-yl)-biphenyl-4-ylmethyl]-3H-imidazo[4,5-b]pyridine] (TM-25659) inhibits adipocyte differentiation by interacting with peroxisome proliferator-activated receptor gamma. 1 TM-25659 was previously shown to decrease weight gain in a high fat (HF) diet-induced obesity (DIO) mouse model. However, the fundamental mechanisms underlying the effects of TM-25659 remain unknown. Therefore, we investigated the effects of TM-25659 on skeletal muscle functions in C2 myotubes and C57BL/6J mice. We studied the molecular mechanisms underlying the contribution of TM-25659 to palmitate (PA)-induced insulin resistance in C2 myotubes. TM-25659 improved PA-induced insulin resistance and inflammation in C2 myotubes. In addition, TM-25659 increased FGF21 mRNA expression, protein levels, and FGF21 secretion in C2 myotubes via activation of GCN2 pathways (GCN2-$phosphoelF2{\alpha}$-ATF4 and FGF21). This beneficial effect of TM-25659 was diminished by FGF21 siRNA. C57BL/6J mice were fed a HF diet for 30 weeks. The HF-diet group was randomly divided into two groups for the next 14 days: the HF-diet and HF-diet + TM-25659 groups. The HF diet + TM-25659-treated mice showed improvements in their fasting blood glucose levels, insulin sensitivity, insulin-stimulated Akt phosphorylation, and inflammation, but neither body weight nor food intake was affected. The HF diet + TM-25659-treated mice also exhibited increased expression of both FGF21 mRNA and protein. These data indicate that TM-25659 may be beneficial for treating insulin resistance by inducing FGF21 in models of PA-induced insulin resistance and HF diet-induced insulin resistance.

• Proceedings of the Microbiological Society of Korea Conference
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• 2005.05a
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• pp.220.4-220
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• 2005