• BMB Reports
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• v.39 no.5
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• pp.578-585
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• 2006

The cDNA of a firefly luciferase from lantern mRNA of Lampyroidea maculata has been cloned, sequenced and functionally expressed. The cDNA has an open reading frame of 1647 bp and codes for a 548-residue-long polypeptide. Noteworthy, sequence comparison as well as homology modeling showed the highest degree of similarity with H. unmunsana and L. mingrelica luciferases, suggesting a close phylogenetic relationship despite the geographical distance separation. The deduced amino acid sequence of the luciferase gene of firefly L. maculata showed 93% identity to H. unmunsana. Superposition of the three-dimensional model of L. maculata luciferase (generated by homology modeling) and three dimensional structure of Photinus pyralis luciferase revealed that the spatial arrangements of Luciferin and ATP-binding residues are very similar. Putative signature of AMP-binding domain among the various firefly species and Lampyroidea maculata was compared and a striking similarity was found. Different motifs and sites have been identified in Lampyroidea maculata by sequence analysis. Expression and purification of luciferase from Lampyroidea maculata was carried out using Ni-NTA Sepharose. Bioluminescence emission spectrum was similar to Photinus pyralis luciferase.

• BMB Reports
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• v.37 no.1
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• pp.28-34
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• 2004

The discovery of biochemical and cellular functions of unannotated gene products begins with a database search of proteins with structure/sequence homologues based on known genes. Very recently, a number of frontier groups in structural biology proposed a new paradigm to predict biological functions of an unknown protein on the basis of its three-dimensional structure on a genomic scale. Structural proteomics (genomics), a research area for structure-based functional discovery, aims to complete the protein-folding universe of all gene products in a cell. It would lead us to a complete understanding of a living organism from protein structure. Two major complementary experimental techniques, X-ray crystallography and NMR spectroscopy, combined with recently developed high throughput methods have played a central role in structural proteomics research; however, an integration of these methodologies together with comparative modeling and electron microscopy would speed up the goal for completing a full dictionary of protein folding space in the near future.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.1136-1141
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• 2003

Due to the lack of digitally usable standards, it has been known to be difficult to handle the biological data. For example, the name of genes and proteins changes over time or has several synonyms indicating different entities. To cope with these problems, several communities, including the Gene Ontology Consortium and PubGene are making their efforts to move science toward the semantic web vision. Although some progress has been made, its expressivity is not sufficient for full-fledged ontological modeling and reasoning. This paper suggests a methodology for representing and extracting biological knowledge by using Web Ontology Language (OWL) as an extension of Resource Description Framework Schema (RDFS). Some benefits of our approach are: (1) to ensure extended sharing of biological meta data on the Web, and (2) to enrich additional expressivity and the semantics of RDFS+OWL.

• BMB Reports
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• v.44 no.1
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• pp.11-21
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• 2011

During the last decade small regulatory RNA (srRNA) emerged as central players in the regulation of gene expression in all kingdoms of life. Multiple pathways for srRNA biogenesis and diverse mechanisms of gene regulation may indicate that srRNA regulation evolved independently multiple times. However, small RNA pathways share numerous properties, including the ability of a single srRNA to regulate multiple targets. Some of the mechanisms of gene regulation by srRNAs have significant effect on the abundance of free srRNAs that are ready to interact with new targets. This results in indirect interactions among seemingly unrelated genes, as well as in a crosstalk between different srRNA pathways. Here we briefly review and compare the major srRNA pathways, and argue that the impact of srRNA is always at the system level. We demonstrate how a simple mathematical model can ease the discussion of governing principles. To demonstrate these points we review a few examples from bacteria and animals.

• Molecules and Cells
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• v.26 no.2
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• pp.121-130
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• 2008

Methamphetamine, a commonly used addictive drug, is a powerful addictive stimulant that dramatically affects the CNS. Repeated METH administration leads to a rewarding effect in a state of addiction that includes sensitization, dependence, and other phenomena. It is well known that susceptibility to the development of addiction is influenced by sources of reinforcement, variable neuroadaptive mechanisms, and neurochemical changes that together lead to altered homeostasis of the brain reward system. These behavioral abnormalities reflect neuroadaptive changes in signal transduction function and cellular gene expression produced by repeated drug exposure. To provide a better understanding of addiction and the mechanism of the rewarding effect, it is important to identify related genes. In the present study, we performed gene expression profiling using microarray analysis in a reward effect animal model. We also investigated gene expression in four important regions of the brain, the nucleus accumbens, striatum, hippocampus, and cingulated cortex, and analyzed the data by two clustering methods. Genes related to signaling pathways including G-protein-coupled receptor-related pathways predominated among the identified genes. The genes identified in our study may contribute to the development of a gene modeling network for methamphetamine addiction.

• Journal of Preventive Medicine and Public Health
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• v.49 no.5
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• pp.253-259
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• 2016

Objectives: Central obesity plays a major role in the development of many chronic diseases, including cardiovascular disease and cancer. Chronic stress may be involved in the pathophysiology of central obesity. Although several large-scale genome-wide association studies have reported susceptibility genes for central adiposity, the effects of interactions between genes and psychosocial stress on central adiposity have rarely been examined. A recent study focusing on Caucasians discovered the novel gene early B-cell factor 1 (EBF1), which was associated with central obesity-related traits via interactions with stress levels. We aimed to evaluate EBF1 gene-by-stress interaction effects on central adiposity traits, including visceral adipose tissue (VAT), in Korean adults. Methods: A total of 1467 Korean adults were included in this study. We selected 22 single-nucleotide polymorphisms (SNPs) in the EBF1 gene and analyzed their interactions with stress on central adiposity using additive, dominant, and recessive genetic modeling. Results: The four SNPs that had strong linkage disequilibrium relationships (rs10061900, rs10070743, rs4704967, and rs10056564) demonstrated significant interactions with the waist-hip ratio in the dominant model ($p_{int}$<0.007). In addition, two other SNPs (rs6556377 and rs13180086) were associated with VAT by interactions with stress levels, especially in the recessive genetic model ($p_{int}$<0.007). As stress levels increased, the mean values of central adiposity traits according to SNP genotypes exhibited gradual but significant changes (p<0.05). Conclusions: These results suggest that the common genetic variants for EBF1 are associated with central adiposity through interactions with stress levels, emphasizing the importance of managing stress in the prevention of central obesity.

• The Korean Journal of Physiology and Pharmacology
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• v.14 no.6
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• pp.353-358
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• 2010

This study demonstrates the ability of magnolol, a hydroxylated biphenyl compound isolated from Magnolia officinalis, to inhibit LPS-induced expression of iNOS gene and activation of NF-${\kappa}B$/Rel in RAW 264.7 cells. Immunohisto-chemical staining of iNOS and Western blot analysis showed magnolol to inhibit iNOS gene expression. Reporter gene assay and electrophoretic mobility shift assay showed that magnolol inhibited NF-${\kappa}B$/Rel transcriptional activation and DNA binding, respectively. Since p38 is important in the regulation of iNOS gene expression, we investigated the possibility that magnolol to target p38 for its anti-inflammatory effects. A molecular modeling study proposed a binding position for magnolol that targets the ATP binding site of p38 kinase (3GC7). Direct interaction of magnolol and p38 was further confirmed by pull down assay using magnolol conjugated to Sepharose 4B beads. The specific p38 inhibitor SB203580 abrogated the LPS-induced NF-${\kappa}B$/Rel activation, whereas the selective MEK-1 inhibitor PD98059 did not affect the NF-${\kappa}B$/Rel. Collectively, the results of the series of experiments indicate that magnolol inhibits iNOS gene expression by blocking NF-${\kappa}B$/Rel and p38 kinase signaling.

• Journal of Korean Neurosurgical Society
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• v.62 no.5
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• pp.493-501
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• 2019

The generation of human induced pluripotent stem cells (iPSCs) from somatic cells using gene transfer opens new areas for precision medicine with personalized cell therapy and encourages the discovery of essential platforms for targeted drug development. iPSCs retain the genome of the donor, may regenerate indefinitely, and undergo differentiation into virtually any cell type of interest using a range of published protocols. There has been enormous interest among researchers regarding the application of iPSC technology to regenerative medicine and human disease modeling, in particular, modeling of neurologic diseases using patient-specific iPSCs. For instance, Parkinson's disease, Alzheimer's disease, and spinal cord injuries may be treated with iPSC therapy or replacement tissues obtained from iPSCs. In this review, we discuss the work so far on generation and characterization of iPSCs and focus on recent advances in the use of human iPSCs in clinical setting.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.2
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• pp.19-28
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• 2019

The purpose of this study is to examine the trends on machine learning and deep learning research in the published journals from the Web of Science Database. To achieve the study purpose, we used the abstracts of 20,664 articles published between 1990 and 2017, which include the word 'machine learning', 'deep learning', and 'artificial neural network' in their titles. Twenty major research topics were identified from topic modeling analysis and they were inclusive of classification accuracy, machine learning, optimization problem, time series model, temperature flow, engine variable, neuron layer, spectrum sample, image feature, strength property, extreme machine learning, control system, energy power, cancer patient, descriptor compound, fault diagnosis, soil map, concentration removal, protein gene, and job problem. The analysis of the time-series linear regression showed that all identified topics in machine learning research were 'hot' ones.

• BMB Reports
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• v.35 no.5
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• pp.498-507
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• 2002

A gene that encodes a thermostable protease, coined thermicin, has been isolated from Thermoanaerobacter yonseiensis that is expressed and characterized in E. coli.. In order to elucidate the molecular characteristics on thermostability of the enzyme, molecular modeling and mutagenesis technology were applied. In the modeling structure, the structural core, including the active site, was well conserved; whereas, the two loop regions were unique when compared to thermitase. The mutant enzyme with the small loop deleted (D190-I196), based on modeling structural information, showed identical enzyme activity. However, when the large loop was deleted (P233-P244), a little lower $K_m$ and even a lower kcat was found. This indicates that the large loop could influence catalytic activity. However, the unfolding temperature ($T_m$), which was determined by a differential-scanning calorimetry for the mutant enzyme deleted the small loop, was $96^{\circ}C$. This is $14^{\circ}C$ lower than that for the parent thermicin. These results suggest that the small loop may play a role in maintaining the proper folding of the enzyme at high temperatures, whereas the large loop might be related to catalysis.