• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.235-235
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• 2022

Genome selection is a promising tool for plant and animal breeding, which uses genome-wide molecular marker data to capture large and small effect quantitative trait loci and predict the genetic value of selection candidates. Genomic selection has been shown previously to have higher prediction accuracies than conventional marker-assisted selection (MAS) for quantitative traits. In this study, the prediction accuracy of 10 agricultural traits in the wheat core group with 567 points was compared. We used a cross-validation approach to train and validate prediction accuracy to evaluate the effects of training population size and training model.As for the prediction accuracy according to the model, the prediction accuracy of 0.4 or more was evaluated except for the SVN model among the 6 models (GBLUP, LASSO, BayseA, RKHS, SVN, RF) used in most all traits. For traits such as days to heading and days to maturity, the prediction accuracy was very high, over 0.8. As for the prediction accuracy according to the training group, the prediction accuracy increased as the number of training groups increased in all traits. It was confirmed that the prediction accuracy was different in the training population according to the genetic composition regardless of the number. All training models were verified through 5-fold cross-validation. To verify the prediction ability of the training population of the wheat core collection, we compared the actual phenotype and genomic estimated breeding value using 35 breeding population. In fact, out of 10 individuals with the fastest days to heading, 5 individuals were selected through genomic selection, and 6 individuals were selected through genomic selection out of the 10 individuals with the slowest days to heading. Therefore, we confirmed the possibility of selecting individuals according to traits with only the genotype for a shorter period of time through genomic selection.

• Mycobiology
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• v.44 no.2
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• pp.105-111
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• 2016

Paclitaxel (taxol) has long been used as a potent anticancer agent for the treatment of many cancers. Ever since the fungal species Taxomyces andreanae was first shown to produce taxol in 1993, many endophytic fungal species have been recognized as taxol accumulators. In this study, we analyzed the taxol-producing capacity of different Colletotrichum spp. to determine the distribution of a taxol biosynthetic gene within this genus. Distribution of the taxadiene synthase (TS) gene, which cyclizes geranylgeranyl diphosphate to produce taxadiene, was analyzed in 12 Colletotrichum spp., of which 8 were found to contain the unique skeletal core structure of paclitaxel. However, distribution of the gene was not limited to closely related species. The production of taxol by Colletotrichum dematium, which causes pepper anthracnose, depended on the method in which the fungus was stored, with the highest production being in samples stored under mineral oil. Based on its distribution among Colletotrichum spp., the TS gene was either integrated into or deleted from the bacterial genome in a species-specific manner. In addition to their taxol-producing capacity, the simple genome structure and easy gene manipulation of these endophytic fungal species make them valuable resources for identifying genes in the taxol biosynthetic pathway.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.2
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• pp.107-112
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• 2013

With the progress of NGS technologies, large genome data have been exploded recently. To analyze such data effectively, the assistance of HPC technique is necessary. In this paper, we organized a genome analysis pipeline to call SNP from NGS data. To organize the pipeline efficiently under HPC environment, we analyzed the CPU utilization pattern of each pipeline steps. We found that sequence alignment is computing centric and suitable for parallelization. We also analyzed the performance of parallel open source alignment tools and found that alignment method utilizing many-core processor can improve the performance of genome analysis pipeline.

• Genomics & Informatics
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• v.8 no.1
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• pp.34-40
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• 2010

Radiofrequency (RF) radiation might induce the transcription of a certain set of genes as other physical stresses like ionizing radiation and UV. To observe transcriptional changes upon RF radiation, we exposed WI-38, human lung fibroblast cell to 1763 MHz of mobile phone RF radiation at 60 W/kg of specific absorption rate (SAR) for 24h with or without heat control. There were no significant changes in cell numbers and morphology after exposure to RF radiation. Using quantitative RT-PCR, we checked the expression of three heat shock protein (HSP) (HSPA1A, HSPA6 and HSP105) and seven stress-related genes (TNFRSF11B, FGF2, TGFB2, ITGA2, BRIP1, EXO1, and MCM10) in RF only and RF/HS groups of RF-exposed cells. The expressions of three heat shock proteins and seven stress-related genes were selectively changed only in RF/HS groups. Based on the expression of ten genes, we could classify thermal and non-thermal effect of RF-exposure, which genes can be used as biomarkers for RF radiation exposure.

• Journal of Microbiology
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• v.43 no.5
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• pp.411-416
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• 2005

The high-throughput sequencing of microbial genomes has resulted in the relatively rapid accumulation of an enormous amount of genomic sequence data. In this context, the problem posed by the detection of promoters in genomic DNA sequences via computational methods has attracted considerable research attention in recent years. This paper addresses the development of a predictive model, known as the dependence decomposition weight matrix model (DDWMM), which was designed to detect the core promoter region, including the -10 region and the transcription start sites (TSSs), in prokaryotic genomic DNA sequences. This is an issue of some importance with regard to genome annotation efforts. Our predictive model captures the most significant dependencies between positions (allowing for non­adjacent as well as adjacent dependencies) via the maximal dependence decomposition (MDD) procedure, which iteratively decomposes data sets into subsets, based on the significant dependence between positions in the promoter region to be modeled. Such dependencies may be intimately related to biological and structural concerns, since promoter elements are present in a variety of combinations, which are separated by various distances. In this respect, the DDWMM may prove to be appropriate with regard to the detection of core promoter regions and TSSs in long microbial genomic contigs. In order to demonstrate the effectiveness of our predictive model, we applied 10-fold cross-validation experiments on the 607 experimentally-verified promoter sequences, which evidenced good performance in terms of sensitivity.

• Journal of Oriental Neuropsychiatry
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• v.26 no.1
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• pp.63-78
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• 2015

Objectives: Pinelliae Rhizoma has traditionally been used as an anti-depressant in oriental medicine. This study is to investigate the effect of Pinelliae Rhizoma extract (PRe) on psychological stress in genome wild expression of mice. Methods: After giving physical stress to mice, PRe was orally administered with 100 mg/kg/day for five days. After extracting whole brain tissue from the mice, their genome changes were observed by micorarray analysis method. The genome changes were analyzed by IMAGENE 4.0, TREEVIEW, FatiGo algorithems, BOND database, cytoscape program, etc. Results: 1. PRe administered group were remained at normal level; 60% of increase was shown in expressed genes by physical stress, and 65% of decrease was shown in expressed genes by psychological stress. 2. Genes with increased expression in control group that remained at a normal state in PRe administered group were involved with the gene of a cellular metabolic process on biological process, protein binding on molecular function, and cell part on cell composition. The pathway was found to be cytokin-cytokin receptor interaction. 3. Genes with decreased expression in control group that remained at a normal state in PRe administered group were involved with the gene of a cellular metabolic process on biologiacl detail and coupled ATPaes activity on molecular function. This gene related path was Ubiquintin mediated proteolysis etc. 4. Core node genes analyzed by protein interaction network were Vinculin, Cell sdivision cycle 42 homolog (S. cerevisiae) etc. They played an important role in maintaining cytoskeleton and controlling cell cycle. Conclusions: Several genes were up-regulated and down-regulated in response to psychological stress. The expression of most of the genes that were altered in response to psychological stress was restored to normal levels in PRe treated mice. When the interaction network information was analyzed, the recovery of the core node genes in PRe treated mice indicates that this final set of genes may be the effective target of PRe.

• Microbiology and Biotechnology Letters
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• v.47 no.1
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• pp.25-33
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• 2019

Lactobacillus rhamnosus BFE5264, isolated from a Maasai fermented milk product ("kule naoto"), was previously shown to exhibit bile acid resistance, cholesterol assimilation, and adhesion to HT29-MTX cells in vitro. In this study, we re-annotated and analyzed the previously reported complete genome sequence of strain BFE5264. The genome consists of a circular chromosome of 3,086,152 bp and a putative plasmid, which is the largest one identified among L. rhamnosus strains. Among the 2,883 predicted protein-coding genes, those with carbohydrate-related functions were the most abundant. Genome analysis of strain BFE5264 revealed two consecutive CRISPR regions and no known virulence factors or antimicrobial resistance genes. In addition, previously known highly variable regions in the genomes of L. rhamnosus strains were also evident in strain BFE5264. Pairwise comparison with the most studied probiotic strain L. rhamnosus GG revealed strain BFE5264-specific deletions, probably due to insertion sequence-mediated recombination. The latter was associated with loss of the spaCBA pilin gene cluster and exopolysaccharide biosynthetic genes. Comparative genomic analysis of the sequences from all available L. rhamnosus strains revealed that they were clustered into two groups, being within the same species boundary based on the average nucleotide identities. Strain BFE5264 had a sister group relationship with the group that contained strain GG, but neither ANI-based hierarchical clustering nor core-gene-based phylogenetic tree construction showed a clear distinctive pattern associated with the isolation source, implying that the genotype alone cannot account for their ecological niches. These results provide insights into the probiotic mechanisms of strain BFE5264 at the genomic level.

• Proceedings of the Korean Society of Sericultural Science Conference
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• 2005.04a
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• pp.37-37
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• 2005

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.31 no.4
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• pp.24-33
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• 2013

• Proceedings of the Korean Society of Sericultural Science Conference
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• 2004.10a
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• pp.65-66
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• 2004