• 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.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.50.4-51
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• 2020

We report our discovery of Raman-scattered He II λ6545 feature in young planetary nebulae NGC 6886 and NGC 6881 which indicates the existence of atomic hydrogen components. Considering sharply increasing cross-section of hydrogen atom near the resonance, Raman-scattered He II features are a useful diagnostic tool to investigate the distribution and kinematics of H I region in planetary nebulae. The high-resolution spectroscopic observation was carried out using BOES installed on the 1.8 m telescope of BOAO. We estimate the column density of H I region and its expansion velocity using our grid-based Monte-Carlo radiative transfer code. We assume that the H I region is uniformly distributed in spherical shell geometry with an opening angle and expands with constant speed. Our best-fit model is shown with the column density NHI = 3 × 1020 cm-2 and expansion speed vexp = 25 km s-1 with the opening angle ~ 25° for NGC 6886, and NHI = 4 × 1020 cm-2 and vexp = 30 km s-1 with the opening angle ~ 35° for NGC 6881. We present brief discussions on the late-stage of evolution of stars with mass > 3 M⊙.

• Interdisciplinary Bio Central
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• v.4 no.1
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• pp.2.1-2.7
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• 2012

Introduction: Histone deacetylases (HDAC) are a class of enzymes that remove acetyl groups from ${\varepsilon}$-N-acetyl lysine amino acids of histone proteins. Their action is opposite to that of histone acetyltransferase that adds acetyl groups to these lysines. Only few HDAC inhibitors are approved and used as anti-cancer therapeutics. Thus, discovery of new and potential HDAC inhibitors are necessary in the effective treatment of cancer. Materials and Methods: This study proposed a method using support vector machine (SVM) to classify HDAC8 inhibitors and non-inhibitors in early-phase virtual compound filtering and screening. The 100 experimentally known HDAC8 inhibitors including 52 inhibitors and 48 non-inhibitors were used in this study. A set of molecular descriptors was calculated for all compounds in the dataset using ADRIANA. Code of Molecular Networks. Different kernel functions available from SVM Tools of free support vector machine software and training and test sets of varying size were used in model generation and validation. Results and Conclusion: The best model obtained using kernel functions has shown 75% of accuracy on test set prediction. The other models have also displayed good prediction over the test set compounds. The results of this study can be used as simple and effective filters in the drug discovery process.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.97-100
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• 2004

The identification of the DNA structure as a double-stranded helix consting of two nucleotide chain molecules was a milestone in modern molecular biology. The DNA chip technology is based on reverse hybridization that follows the principle of complementary binding of double-stranded DNA. DNA chip can be described as the deposition of defined nucleic acid sequences, probes, on a solid substrate to form a regular array of elements that are available for hybridization to complementary nucleic acids, targets. DNA chips based on cDNA clons, oligonucleotides and genomic clons have been developed for gene expression studies, genetic variation analysis and genomic changes associated with disease including cancers and genetic diseases. DNA chips for gene expression profiling can be used for functional analysis in human eel Is and animal models, disease-related gene studies, assessment of gene therapy, assessment of genetically modified food, and research for drug discovery. DNA chips for genetic variation detection can be used for the detection of mutations or chromosomal abnormalities in cnacers, drug resistances in cancer cells or pathogenic microbes, histocompatibility analysis for transplantation, individual identification for forensic medicine, and detection and discrimination of pathogenic microbes. The DNA chip will be generalized as a useful tool in clinical diagnostics in near future. Lab-on-a chip and informatics will facilitate the development of a variety of DNA chips for diagnostic purpose.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.271-272
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• 2014

As E-discovery in criminal investigation is increasing, the importance of Forensic Tools which can legally extract data with high effectiveness is getting higher. Digital products are growing fast. Therefore, Forensic Tools should be implemented readily to suit users and events well. Although forensic industry and governments use expensive forensic tools, some have suggested limitations to its use, such as memory limitations and the limits of post-audit. We need to develop open source forensic tools that can implement a variety of forensic tool fast. This research studies digital forensics technical skills which are commercialized currently and suggests applicable strategies of the open digital forensics to help overcome these limitations.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.119-124
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• 2004

Real data as web log file tend to be incomplete. But we have to find useful knowledge from these for optimal decision. In web log data, many useful things which are hyperlink information and web usages of connected users may be found. The size of web data is too huge to use for effective knowledge discovery. To make matters worse, they are very sparse. We overcome this sparse problem using Markov Chain Monte Carlo method as multiple imputations. This missing value imputation changes spare web data to complete. Our study may be a useful tool for discovering knowledge from data set with sparseness. The more sparseness of data in increased, the better performance of MCMC imputation is good. We verified our work by experiments using UCI machine learning repository data.

• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.153-170
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• 2008

Customers' needs change every moment. Profitability of stores can't be increased anymore with an existing standardized chain store management. Accordingly, a personalized store management tool needs through prediction of customers' preference. In this study, we propose a recommending procedure using dynamic customers' preference by analyzing the transaction database. We utilize self-organizing map algorithm and association rule mining which are applied to cluster the chain stores and explore purchase sequence of customers. We demonstrate that the proposed methodology makes an effect on recommendation of products in the market which is characterized by a fast fashion and a short product life cycle.

• CELLMED
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• v.6 no.4
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• pp.24.1-24.4
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• 2016

The emergence of influenza virus and antigenic drift are potential cause of world-wide pandemic. There are some commercially available drugs in the market to treat influenza. During past decade, however, critical resistances have been raised for biological targets. Because of structural complexity and flexibility of target proteins, applying a computational modeling tool is very beneficial for developing alternative anti-influenza drugs. In this review, we introduced molecular dynamics (MD) simulations approach to reflect full conformational flexibility of proteins during molecular modeling works. Case studies of MD works were summarized for the drug discovery and drug resistance mechanism of anti-influenza pharmaceuticals.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.12
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• pp.7057-7063
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• 2013

The discovery of the immunodeficient mice has provided a tool for establishing animal models as hosts for in vivo analysis of AML. Various model systems have been established in the last few decades, and it is essential that murine AML models are developed to exploit more specific, targeted therapeutics. In this review, we concentrate on the models of AML and discuss the development of immunodeficiency models for understanding of leukemogenesis, describe those now available and their values and document the methods used for establishing and identifying AML mice models, as well as factors influencing engraftment of human AML in immunodeficient mice. Thus, the function of this article is to provide clinicians and experimentalists with a chronological, comprehensive appraisal of all AML model systems.

• Animal cells and systems
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• v.11 no.2
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• pp.99-104
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• 2007

RNA interference (RNAi) is the phenomenon of gene silencing by double-stranded RNA (dsRNA) at transcriptional and post-transcriptional levels in a sequence-specific manner. Reverse genetic approaches using RNA interference (RNAi) have become a major tool for biological researches since its discovery in the nematode Caenorhabditis elegans. In this review, we overview how the RNAi phenomenon was discovered and how the underlying mechanism has been elucidated. We also describe and discuss how RNAi experiments can be performed and how RNAi can be used for genetic studies.