• Journal of KIISE:Software and Applications
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• v.35 no.6
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• pp.347-356
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• 2008

High-throughput microarray is one of the most popular tools in molecular biology, and various computational methods have been developed for the microarray data analysis. While the computational methods easily extract significant features, it suffers from inferring modules of multiple co-regulated genes. Hypernetworhs are motivated by biological networks, which handle all elements based on their combinatorial processes. Hence, the hypernetworks can naturally analyze the biological effects of gene combinations. In this paper, we introduce a hypernetwork classifier for microRNA (miRNA) profile analysis based on microarray data. The hypernetwork classifier uses miRNA pairs as elements, and an evolutionary learning is performed to model the microarray profiles. miTNA modules are easily extracted from the hypernetworks, and users can directly evaluate if the miRNA modules are significant. For experimental results, the hypernetwork classifier showed 91.46% accuracy for miRNA expression profiles on multiple human canters, which outperformed other machine learning methods. The hypernetwork-based analysis showed that our approach could find biologically significant miRNA modules.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.1
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• pp.141-153
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• 2016

The increase in frequency and scale of natural disasters is the typical negative examples of the global climate change and the change of the human living environment in cities. The damage caused by natural disasters in particular including human and physical damage is directly linked to the safety and properties of citizens. Besides, the damage may occur to SOC facilities directly or indirectly. The SOC facilities damaged by disasters cause infringement of citizens safety rights. Therefore, a plan to provide prompt and effective risk map information by linking a 3D disaster information display system, which handles the information of the damage that may occur to SOC facilities such as bridges, beams, and dams at the time of disasters, with an on-site assistance application is suggested in this study. The prompt provision of risk map information is defined as a dynamic expression technology in this study. Also, disaster information is processed and compressed with a module developed to be linked organically to a system that displays disaster information, a proliferation system that can use the information on site, and a DB system that constructs a relationship with the information. Based on the module, the effective disaster information compression plan will be prepared, and the prompt information transmission system will be secured in the future.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.111-111
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• 2017

The development and productivity of maize (Zea mays L.) is frequently impacted by water scarcity, and consequently to increased drought tolerance in a priority target in maize breeding programs. To elucidate the molecular mechanisms of resistance to drought stress in maize, RNA-seq of the public database was used for transcriptome profiling of the seedling stage exposed to drought stress of three levels, such as moderate, severe drought stress and re-watering. In silico analysis of differentially expressed genes (DEGs), 176 up-regulated and 166 down-regulated DEGs was detected at moderated stress in tolerance type. These DEGs was increasing degradation of amino acid metabolism in biological pathways. Six modules based on a total of 4,771 DEGs responses to drought stress by the analysis of co-expression network between tolerance and susceptible type was constructed and showed to similar module types. These modules were discriminated yellow, greenyellow, turquoise, royalblue, brown4 and plum1 with 318, 2433, 375, 183, 1405 and 56 DEGs, respectively. This study was selected 30 DEGs to predicted drought stress response gene and was evaluated expression levels using drought stress treated sample and re-watering sample by quantitative Real-Time Polymerase Chain Reaction (qRT-PCR). 23 genes was shown increasing with drought stress and decreasing with re-watering. This study contribute to a better understanding of the molecular mechanisms of maize seedling stage responses to drought stress and could be useful for developing maize cultivar resistant to drought stress.

• Journal of Life Science
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• v.30 no.1
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• pp.45-57
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• 2020

The prenatal period in livestock animals is crucial for meat production because net increase in the number of muscle fibers is finished before birth. However, there is no study on the growth and development mechanism of muscles in Hanwoo during this period. Therefore, to find candidate genes involved in muscle growth and development during this period in Hanwoo, mRNA expression data of longissimus in Hanwoo at 6 and 9 months post-conceptional age (MPA) were analyzed. We independently identified differentially expressed genes (DEGs) using DESeq2 and edgeR which are R software packages, and considered the overlaps of the results as final-DEGs to use in downstream analysis. The DEGs were classified into several modules using WGCNA then the modules' functions were analyzed to identify modules which involved in myogenesis and adipogenesis. Finally, the hub genes which had the highest WGCNA module membership among the top 10% genes of the STRING network maximal clique centrality were identified. 913(6 MPA specific DEGs) and 233(9 MPA specific DEGs) DEGs were figured out, and these were classified into five and two modules, respectively. Two of the identified modules'(one was in 6, and another was in 9 MPA specific modules) functions was found to be related to myogenesis and adipogenesis. One of the hub genes belonging to the 6 MPA specific module was axin1 (AXIN1) which is known as an inhibitor of Wnt signaling pathway, another was succinate-CoA ligase ADP-forming beta subunit (SUCLA2) which is known as a crucial component of citrate cycle.