• Macromolecular Research
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• v.17 no.2
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• pp.110-115
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• 2009

The electrical, morphological and rheological properties of melt and dry mixed composites of poly ethylene (PE)/graphite (Gr), polypropylene (PP)/Gr and PP/nickel-coated carbon fiber (NCCF) were investigated as a function of filler type, filler content and processing temperature. The electrical conductivities of dry mixed PP/NCCF composites were increased with decreasing processing temperature. For the melt mixed PP/NCCF composites, the electrical conductivities were higher than those of the melt mixed PE/Gr and PP/Gr composites, which was attributed to the effect of the higher NCCF aspect ratio in allowing the composites to form a more conductive network in the polymer matrix than the graphite does. From the results of morphological studies, the fillers in the dry mixed PP/NCCF composites were more randomly dispersed compared to those in the melt mixed PP/NCCF composites. The increased electrical conductivities of the dry mixed composites were attributed to the more random dispersion of NCCF compared to that of the melt mixed PP/NCCF composites. The complex viscosities of the PP/Gr composites were higher than those of the PP/NCCF composites, which was attributed to the larger diameter of the graphite particles than that of the NCCF. Furthermore, the fiber orientation in the 'along the flow' direction during melt mixing was attributed to the decreased complex viscosities of the melt mixed PP/NCCF composites compared those of the melt mixed PP/Gr composites.

• Journal of Plant Biotechnology
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• v.37 no.4
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• pp.472-482
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• 2010

For the massive screening of the genes related to oxidative stress, a cDNA library was constructed from hot pepper (Capsicum annuum L. cv. Nockkwang) leaves treated with methyl viologen. From this library, 1,589 cDNA clones were sequenced from their 5' ends. The sequences were clustered into 1,252 unigenes comprised of 152 contigs and 1,100 singletons. Similarity search against NCBI protein database identified 1,005 ESTs (80.3%) as Known, 197 ESTs (15.7%) as Unknown, and 50 ESTs (3.99%) as No hit. In the ESTs, oxidative stress-related genes such as ascorbate peroxidase, catalase, and osmotin precursor were highly expressed. The cDNA microarray containing 1,252 unigenes was constructed and used to analyze their expression upon methyl viologen treatment. Analyses of the hybridization revealed that various stress-related genes such as peroxidase, tyrosine aminotransferase, and omega-6 fatty acid desaturase, were induced and some metabolism related genes such as aldolase and ketol-acid reductoisomerase, were repressed by methyl viologen treatment, respectively. The information from this study will be used for further study on the functional roles of oxidative stress-related genes and signaling network of oxidative stress in hot pepper.

• Genomics & Informatics
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• v.14 no.4
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• pp.222-229
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• 2016

Kimchi is a traditional Korean food prepared by fermenting vegetables, such as Chinese cabbage and radishes, which are seasoned with various ingredients, including red pepper powder, garlic, ginger, green onion, fermented seafood (Jeotgal), and salt. The various unique microorganisms and bioactive components in kimchi show antioxidant activity and have been associated with an enhanced immune response, as well as anti-cancer and anti-diabetic effects. Red pepper inhibits decay due to microorganisms and prevents food from spoiling. The vast amount of biological information generated by academic and industrial research groups is reflected in a rapidly growing body of scientific literature and expanding data resources. However, the genome, biological pathway, and related disease data are insufficient to explain the health benefits of kimchi because of the varied and heterogeneous data types. Therefore, we have constructed an appropriate semantic data model based on an integrated food knowledge database and analyzed the functional and biological processes associated with kimchi in silico. This complex semantic network of several entities and connections was generalized to answer complex questions, and we demonstrated how specific disease pathways are related to kimchi consumption.

• Molecules and Cells
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• v.27 no.6
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• pp.629-634
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• 2009

G protein-coupled receptors (GPCRs) are part of multi-protein networks called 'receptosomes'. These GPCR interacting proteins (GIPs) in the receptosomes control the targeting, trafficking and signaling of GPCRs. PDZ domain proteins constitute the largest protein family among the GIPs, and the predominant function of the PDZ domain proteins is to assemble signaling pathway components into close proximity by recognition of the last four C-terminal amino acids of GPCRs. We present here a machine learning based approach for the identification of GPCR-binding PDZ domain proteins. In order to characterize the network of interactions between amino acid residues that contribute to the stability of the PDZ domain-ligand complex and to encode the complex into a feature vector, amino acid contact matrices and physicochemical distance matrix were constructed and adopted. This novel machine learning based method displayed high performance for the identification of PDZ domain-ligand interactions and allowed the identification of novel GPCR-PDZ domain protein interactions.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.476-479
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• 2008

Understanding the dynamics of proteins is essential to gain insight into biological functions of proteins. The protein dynamics is delineated by conformational fluctuation (i.e. thermal vibration), and thus, thermal vibration of proteins has to be understood. In this paper, a simple mechanical model was considered for understanding protein's dynamics. Specifically, a mechanical vibration model was developed for understanding the large protein dynamics related to biological functions. The mechanical model for large proteins was constructed based on simple elastic model (i.e. Tirion's elastic model) and model reduction methods (dynamic model condensation). The large protein structure was described by minimal degrees of freedom on the basis of model reduction method that allows one to transform the refined structure into the coarse-grained structure. In this model, it is shown that a simple reduced model is able to reproduce the thermal fluctuation behavior of proteins qualitatively comparable to original molecular model. Moreover, the protein's dynamic behavior such as collective dynamics is well depicted by a simple reduced mechanical model. This sheds light on that the model reduction may provide the information about large protein dynamics, and consequently, the biological functions of large proteins.

• Microbiology and Biotechnology Letters
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• v.47 no.1
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• pp.1-10
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• 2019

Saline soils comprise more than half a billion hectares worldwide. Thus, they warrant attention for their efficient, economical, and environmentally acceptable management. Halophytes are being progressively utilized for human benefits. The halophyte microbiome contributes significantly to plant performance and can provide information regarding complex ecological processes involved in the osmoregulation of halophytes. Microbial communities associated with the rhizosphere, phyllosphere, and endosphere of halophytes play an important role in plant health and productivity. Members of the plant microbiome belonging to domains Archaea, Bacteria, and kingdom Fungi are involved in the osmoregulation of halophytes. Halophilic microorganisms principally use compatible solutes, such as glycine, betaine, proline, trehalose, ectoine, and glutamic acid, to survive under salinity stress conditions. Plant growth-promoting rhizobacteria (PGPR) enhance plant growth and help to elucidate tolerance to salinity. Detailed studies of the metabolic pathways of plants have shown that plant growth-promoting rhizobacteria contribute to plant tolerance by affecting the signaling network of plants. Phytohormones (indole-3-acetic acid and cytokinin), 1-aminocyclopropane-1-carboxylic acid deaminase biosynthesis, exopolysaccharides, halocins, and volatile organic compounds function as signaling molecules for plants to elicit salinity stress. This review focuses on the functions of plant microbiome and on understanding how the microorganisms affect halophyte health and growth.

• Journal of Microbiology and Biotechnology
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• v.33 no.9
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• pp.1141-1148
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• 2023

Herein, we explored the potential of the apple's core microbiota for biological control of Erwinia amylovora, which causes fire blight disease, and analyzed the structure of the apple's bacterial community across different tissues and seasons. Network analysis results showed distinct differences in bacterial community composition between the endosphere and rhizosphere of healthy apples, and eight taxa were identified as negatively correlated with E. amylovora, indicating their potential key role in a new control strategy against the pathogen. This study highlights the critical role of the apple's bacterial community in disease control and provides a new direction for future research in apple production. In addition, the findings suggest that using the composition of the apple's core taxa as a biological control strategy could be an effective alternative to traditional chemical control methods, which have been proven futile and environmentally harmful.

• Journal of Biomedical Engineering Research
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• v.20 no.4
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• pp.435-442
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• 1999

A fuzzy-ART(adaptive resonance theory) network for the PVC(premature ventricular contraction) classification using wavelet coefficient is designed. This network consists of the feature extraction and learning of the fuzzy-ART network. In the first step, we have detected the QRS from the ECG signal in order to set the threshold range for feature extraction and the detected QRS was divided into several frequency bands by wavelet transformation using Haar wavelet. Among the low-frequency bands, only the 6th coefficient(D6) are selected as the input feature. After that, the fuzzy-ART network for classification of the PVC is learned by using input feature which comprises of binary data converted by applying threshold to D6. The MIT/BIH database including the PVC is used for the evaluation. The designed fuzzy-ART network showed the PVC classification ratio of 96.52%.

• Journal of Physiology & Pathology in Korean Medicine
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• v.35 no.5
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• pp.125-131
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• 2021

The scientific understanding of Korean medicine theory remains largely unknown, since there is a lack of proper methods to investigate its complex and unique characteristics. Here, we introduce a drug-centered approach, a novel method to investigate Korean medicine theory by analyzing the mechanisms of herbal medicines. This method can be effectively conducted by employing network pharmacology that can analyze the systems-level mechanisms of herbal medicines on a large scale. Firstly, we introduce the method of network pharmacology that are applied to analyze the mechanisms of herbal medicines in a step-by-step manner. Then, we show how the drug-centered approach employing network pharmacology can be applied to investigate Korean medicine theory by describing studies that identify the biological correlates of the cold-hot nature of herbs, spleen qi deficiency syndrome, or Sasang constitution. Finally, we discuss the limitations and future directions of the proposed approach in two aspects: The methods of network pharmacology for a drug-centered approach and the process of inferring Korean medicine theory through it. We believe that a drug-centered approach employing network pharmacology will provide an advanced scientific understanding of Korean medicine theory and contribute to its development by generating biologically plausible hypothesis.

• The Journal of Korean Medicine
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• v.45 no.1
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• pp.114-125
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• 2024

Objectives: Network pharmacology is an analysis method that explores drug-centered efficacy and mechanism by constructing a compound-target-disease network based on system biology, and is attracting attention as a methodology for studying herbal medicine that has the characteristics for multi-compound therapeutics. Thus, we investigated the potential functions and pathways of Myrrha on Allergic Rhinitis (AR) via network pharmacology analysis and molecular docking. Methods: Using public databases and PubChem database, compounds of Myrrha and their target genes were collected. The putative target genes of Myrrha and known target genes of AR were compared and found the correlation. Then, the network was constructed using STRING database, and functional enrichment analysis was conducted based on the Gene Ontology (GO) Biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways. Binding-Docking stimulation was performed using CB-Dock. Results: The result showed that total 3 compounds and 55 related genes were gathered from Myrrha. 33 genes were interacted with AR gene set, suggesting that the effects of Myrrha are closely related to AR. Target genes of Myrrha are considerably associated with various pathways including 'Fc epsilon RI signaling pathway' and 'JAK-STAT signaling pathway'. As a result of blinding docking, AKT1, which is involved in both mechanisms, had high binding energies for abietic acid and dehydroabietic acid, which are components of Myrrha. Conclusion: Through a network pharmacological method, Myrrha was predicted to have high relevance with AR by regulating AKT1. This study could be used as a basis for studying therapeutic effects of Myrrha on AR.