• Journal of KIISE:Databases
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• v.31 no.3
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• pp.205-218
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• 2004

As the development of database technology for managing spatiotemporal data, new types of spatiotemporal application services that need the spatiotemporal knowledge discovery from the large volume of spatiotemporal data are emerging. In this paper, a new 3-layered discovery framework for the development of spatiotemporal knowledge discovery techniques is proposed. The framework supports the foundation model in order not only to define spatiotemporal knowledge discovery problem but also to represent the definition of spatiotemporal knowledge and their relationships. Also the components of spatiotemporal knowledge discovery system and its implementation model are proposed. The discovery framework proposed in this paper satisfies the requirement of the development of new types of spatiotemporal knowledge discovery techniques. The proposed framework can support the representation model of each element and relationships between objects of the spatiotemporal data set, information and knowledge. Hence in designing of the new types of knowledge discovery such as spatiotemporal moving pattern, the proposed framework can not only formalize but also simplify the discovery problems.

• Biomolecules & Therapeutics
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• v.21 no.6
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• pp.411-422
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• 2013

G-protein-coupled receptors (GPCR) are the largest superfamily of receptors responsible for signaling between cells and tissues, and because they play important physiological roles in homeostasis, they are major drug targets. New technologies have been developed for the identification of new ligands, new GPCR functions, and for drug discovery purposes. In particular, intercellular lipid mediators, such as, lysophosphatidic acid and sphingosine 1-phosphate have attracted much attention for drug discovery and this has resulted in the development of fingolimod (FTY-720) and AM095. The discovery of new intercellular lipid mediators and their GPCRs are discussed from the perspective of drug development. Lipid GPCRs for lysophospholipids, including lysophosphatidylserine, lysophosphatidylinositol, lysophosphatidylcholine, free fatty acids, fatty acid derivatives, and other lipid mediators are reviewed.

• KDI Journal of Economic Policy
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• v.41 no.4
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• pp.45-66
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• 2019

This paper empirically examines what role of existing exporters play in the discovery of new export products and whether there are evidence of spillovers from export discovery. We find that existing exporters are more likely to discover new export products than non-exporters. We also find evidence of export discovery spillovers; export discovery of a product by some plants had an effect of increasing the probability of subsequent export market penetration of the same product by other plants. Export discovery spillovers are found to be stronger among geographically closely located plants. We argue that information spillovers is a part of the story: you learn from your neighboring discoverers about the profitability of potentially exportable products.

• Journal of the Korea Society of Computer and Information
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• v.25 no.10
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• pp.51-58
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• 2020

The DDS discovery is a behind-the-scenes way in which DDS objects on different nodes find out each other in a same domain. If the DDS discovery takes a long time, the preparation time for DDS communication is also delayed. And if the DDS discovery between several nodes fails, DDS communication between nodes related to them would be also failed. This problems can be a big cause of overall system performance degradation. Therefore, the improvement of performance for the DDS discovery gives the effect that improves the performance of the entire system. In this paper, I propose an efficient new method which improves the performance and reduces the time of DDS discovery. I simulate both the origin and the new proposed method for DDS discovery, and I compare the result of performance. This result will help for improving a DDS discovery in a large-scale system.

• Natural Product Sciences
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• v.19 no.2
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• pp.150-154
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• 2013

A new oleanane-type triterpenoid saponin together with six known saponins were isolated from the roots of Pulsatilla cernua. Their structures were elucidated on the basis of spectroscopic data, including 2D NMR spectra and chemical evidence. Compounds 1 and 6 are reported from this genus for the first time.

• Biomolecules & Therapeutics
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• v.22 no.5
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• pp.400-405
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• 2014

G-protein coupled receptor 119 (GPR119) has emerged as a novel target for the treatment of type 2 diabetes mellitus. GPR119 is involved in glucose-stimulated insulin secretion (GSIS) from the pancreatic b-cells and intestinal cells. In this study, we identified a novel small-molecule GPR119 agonist, HD047703, which raises intracellular cAMP concentrations in pancreatic ${\beta}$-cells and can be expected to potentiate glucose-stimulated insulin secretion from human GPR119 receptor stably expressing cells (CHO cells). We evaluated the acute efficacy of HD047703 by the oral glucose tolerance test (OGTT) in normal C57BL/6J mice. Then, chronic administrations of HD047703 were performed to determine its efficacy in various diabetic rodent models. Single administration of HD047703 caused improved glycemic control during OGTT in a dose-dependent manner in normal mice, and the plasma GLP-1 level was also increased. With respect to chronic efficacy, we observed a decline in blood glucose levels in db/db, ob/ob and DIO mice. These results suggest that HD047703 may be a potentially promising anti-diabetic agent.

• Proceedings of the PSK Conference
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• 2001.04a
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• pp.241.2-241.2
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• 2001

• Proceedings of the Korean Information Science Society Conference
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• 2007.10b
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• pp.17-21
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• 2007

Drug discovery is a long process with a low rate of successful new therapeutic discovery regardless of the advances in information technologies. Identification of candidate proteins is an essential step for the drug discovery and it usually requires considerable time and efforts in the drug discovery. The drug discovery is not a logical, but a fortuitous process. Nevertheless, considerable amount of information on drugs are accumulated in UniProt, NCBI, or DrugBank. As a result, it has become possible to try to devise new computational methods classifying drug target candidates extracting the common features of known drug target proteins. In this paper, we devise a method for drug target protein classification by using weighted feature summation and Support Vector Machine. According to our evaluation, the method is revealed to show moderate accuracy $85{\sim}90%$. This indicates that if the devised method is used appropriately, it can contribute in reducing the time and cost of the drug discovery process, particularly in identifying new drug target proteins.

• Biomolecules & Therapeutics
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• v.22 no.4
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• pp.267-274
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• 2014

Drug development and preclinical trials are challenging processes and more than 80% to 90% of drug candidates fail to gain approval from the United States Food and Drug Administration. Predictive and efficient tools are required to discover high quality targets and increase the probability of success in the process of new drug development. One such solution to the challenges faced in the development of new drugs and combination therapies is the use of low-cost and experimentally manageable in vivo animal models. Since the 1980's, scientists have been able to genetically modify the mouse genome by removing or replacing a specific gene, which has improved the identification and validation of target genes of interest. Now genetically engineered mouse models (GEMMs) are widely used and have proved to be a powerful tool in drug discovery processes. This review particularly covers recent fascinating technologies for drug discovery and preclinical trials, targeted transgenesis and RNAi mouse, including application and combination of inducible system. Improvements in technologies and the development of new GEMMs are expected to guide future applications of these models to drug discovery and preclinical trials.

• Proceedings of the Korean Society of Applied Pharmacology
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• 1994.11a
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• pp.93-98
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• 1994

Most drug discovery has focused in recent years on the development of molecules that either interact with or block receptors, proteins that act as on-off switches for genetic activity, on the surfaces of human cells. Now, we have developed a technology that targets “receptors inside the cell” (intracellular receptors), opening a new and compelling avenue for drug discovery. Our receptor-based small molecule drugs can be catagorized in two ways: 1) receptor agonists, or molecules that activate a receptor; and 2) receptor antagonists, or drugs that inactivate a receptor.