• Korean Journal of Microbiology
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• v.43 no.4
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• pp.325-330
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• 2007

RNase E is an essential Escherichia coli endoribonuclease that plays a major role in the decay and processing of a large fraction of RNAs in the cell and expression of N-terminal domain consisted of 1-498 amino acids (N-Rne) is sufficient to support normal cellular growth. By utilizing these properties of RNase E, we developed a genetic system to screen for amino acid substitutions in the catalytic domain of the protein (N-Rne) that lead to various phenotypes. Using this system, we identified three kinds of mutants. A mutant N-Rne containing amino acid substitution in the S1 domain (I6T) of the protein was not able to support survival of E. coli cells, and another mutant N-Rne with amino acid substitution at the position 488 (R488C) in the small domain enabled N-Rne to have an elevated ribonucleolytic activity, while amino acid substitution in the DNase I domain (N305D) only enabled N-Rne to support survival of E. roli cells when the mutant N-Rne was over-expressed. Analysis of copy number of ColEl-type plasmid revealed that effects of amino acid substitution on the ability of N-Rne to support cellular growth stemmed from their differential effects on the ribonucleolytic activity of N-Rne in the cell. These results imply that the genetic system developed in this study can be used to isolate mutant RNase E with various phenotypes, which would help to unveil a functional role of each subdomain of the protein in the regulation of RNA stability in E. coli.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.121-139
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• 2014

Predicting corporate failure has been an important topic in accounting and finance. The costs associated with bankruptcy are high, so the accuracy of bankruptcy prediction is greatly important for financial institutions. Lots of researchers have dealt with the topic associated with bankruptcy prediction in the past three decades. The current research attempts to use ensemble models for improving the performance of bankruptcy prediction. Ensemble classification is to combine individually trained classifiers in order to gain more accurate prediction than individual models. Ensemble techniques are shown to be very useful for improving the generalization ability of the classifier. Bagging is the most commonly used methods for constructing ensemble classifiers. In bagging, the different training data subsets are randomly drawn with replacement from the original training dataset. Base classifiers are trained on the different bootstrap samples. Instance selection is to select critical instances while deleting and removing irrelevant and harmful instances from the original set. Instance selection and bagging are quite well known in data mining. However, few studies have dealt with the integration of instance selection and bagging. This study proposes an improved bagging ensemble based on instance selection using genetic algorithms (GA) for improving the performance of SVM. GA is an efficient optimization procedure based on the theory of natural selection and evolution. GA uses the idea of survival of the fittest by progressively accepting better solutions to the problems. GA searches by maintaining a population of solutions from which better solutions are created rather than making incremental changes to a single solution to the problem. The initial solution population is generated randomly and evolves into the next generation by genetic operators such as selection, crossover and mutation. The solutions coded by strings are evaluated by the fitness function. The proposed model consists of two phases: GA based Instance Selection and Instance based Bagging. In the first phase, GA is used to select optimal instance subset that is used as input data of bagging model. In this study, the chromosome is encoded as a form of binary string for the instance subset. In this phase, the population size was set to 100 while maximum number of generations was set to 150. We set the crossover rate and mutation rate to 0.7 and 0.1 respectively. We used the prediction accuracy of model as the fitness function of GA. SVM model is trained on training data set using the selected instance subset. The prediction accuracy of SVM model over test data set is used as fitness value in order to avoid overfitting. In the second phase, we used the optimal instance subset selected in the first phase as input data of bagging model. We used SVM model as base classifier for bagging ensemble. The majority voting scheme was used as a combining method in this study. This study applies the proposed model to the bankruptcy prediction problem using a real data set from Korean companies. The research data used in this study contains 1832 externally non-audited firms which filed for bankruptcy (916 cases) and non-bankruptcy (916 cases). Financial ratios categorized as stability, profitability, growth, activity and cash flow were investigated through literature review and basic statistical methods and we selected 8 financial ratios as the final input variables. We separated the whole data into three subsets as training, test and validation data set. In this study, we compared the proposed model with several comparative models including the simple individual SVM model, the simple bagging model and the instance selection based SVM model. The McNemar tests were used to examine whether the proposed model significantly outperforms the other models. The experimental results show that the proposed model outperforms the other models.

• Korean Journal of Plant Resources
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• v.21 no.1
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• pp.1-4
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• 2008

The clonal variation in female flowering was studied in Larix leptolepis clone bank, consisting of 116 clones, for three years. The between-year variation was large; i.e. the percentage of flowering grafts and average number of flowering per graft were $28.4{\sim}67.2$ and $9{\sim}176$, respectively. Differences in flowering abundance among clones were large and statistically significant in all the years studied. The variance of flowering abundance among clones was increased when flowering was poor. The average of broad-sense heritability of flowering abundance was 0.52. The genetic gain(%G) was estimated at 57.4% when the upper 30% clones were selected. The clonal stability of flowering abundance was compared using average number of flowering and coefficient of variance value of each clone. The clones such as Gyeonggi 9(29), Kangwon 37(137), Chungnam 6(46), Chungnam 14(414), R11, R8 showed abundant flowering and high stability.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.2
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• pp.128-136
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• 2006

This study was conducted for developing the stability parameter in uncontrolled landfill by using a biomolecular investigation on the microbial community growing through leachate plume. Landfill J(which is in Cheonan) and landfill T(which is in Wonju) were chosen for this study among a total of 244 closed uncontrolled landfills. It addressed the genetic diversity of the microbial community in the leachate by 165 rDNA gene cloning using PCR and compared quantitative analysis of denitrifiers and methanotrophs with the conventional water quality parameters. From the BLAST search, genes of 47.6% in landfill J, and 32.5% in landfill T, respectively, showed more than 97% of the similarity where Proteobacteria phylum was most significantly observed. It showed that the numbers of denitrification genes, i.e. nirS gene and cnorB gene in the J site are 7 and 4 times higher than those in T site, which is well reflecting from a difference of site closure showing 7 and 13 years after being closed, respectively. In addition, the quantitative analysis on methane formation gene showed that J1 spot immediately bordering with the sources has the greatest number of methane formation bacteria, and it was decreased rapidly according to distribute toward the outer boundary of landfill. The comparative investigation between the number of genes, i.e. nirS gene, cnorB gene and MCR gene, md the conventional monitoring parameters, i.e. TOC, $NH_3-N,\;NO_3-N,\;NO_2-N,\;Cl^-$, alkalinity, addressed that more than 99% of the correlation was observed except for the $NO_3-N$. It was concluded that biomolecular investigation was well consistent with the conventional monitoring parameters to interpret their influences and stability made by leachate plume formed in downgradient around the uncontrolled sites.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.62 no.4
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• pp.333-345
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• 2017

The potato tuber is known as a rich source of essential nutrients, used throughout the world. Although potato-breeding programs share some priorities, the major objective is to increase the genetic potential for yield through breeding or to eliminate hazards that reduce yield. Glycoalkaloids, which are considered a serious hazard to human health, accumulate naturally in potatoes during growth, harvesting, transportation, and storage. Here, we used the AMMI (additive main effects and multiplicative interaction) and GGE (Genotype main effect and genotype by environment interaction) biplot model, to evaluate tuber yield stability and glycoalkaloid content in six potato cultivars across three locations during 2012/2013. The environment on tuber yield had the greatest effect and accounted for 33.0% of the total sum squares; genotypes accounted for 3.8% and $G{\times}E$ interaction accounted for 11.1% which is the nest highest contribution. Conversely, the genotype on glycoalkaloid had the greatest effect and accounted for 82.4% of the total sum squares), whereas environment and $G{\times}E$ effects on this trait accounted for only 0.4% and 3.7%, respectively. Furthermore, potato genotype 'Superior', which covers most of the cultivated area, exhibited high yield performance with stability. 'Goun', which showed lower glycoalkaloid content, was the most suitable and desirable genotype. Results showed that, while tuber yield was more affected by the environment, glycoalkaloid content was more dependent on genotype. Further, the use of the AMMI and GGE biplot model generated more interactive visuals, facilitated the identification of superior genotypes, and suggested decisions on a variety of recommendations for specific environments.

• The Korean Journal of Mycology
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• v.25 no.2 s.81
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• pp.143-151
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• 1997

Interspecific hybrids between Aspergillus niger and Penicillium notatum (Tyr-), hyperlipolytic enzyme-producing fungi, were obtained by nuclear transfer technique. Optimal conditions for formation of intergeneric hybrids were investigated. Maximum production of protoplasts was obtained by 1% Novozyme 234 at $30^{\circ}C$ for 3 hrs and the most effective osmotic stabilizers for the isolation of protoplasts were 0.6 M KCl. Frequencies of hybrid formation by nuclear transfer were $3.8{\times}10^{-3}{\sim}1.3{\times}10^{-3}$. From the observation of genetic stability, conidial size, DNA content, and nuclear stain, it was suggested that their karyotypes are aneuploid. The hybrids showed $1.2{\sim}1.7$ fold higher lipase activities than parental strains. It was strongly supported by results of this study that nuclear transfer technique is much more efficient in the formation of intergeneric hybrids than protoplast fusion and is very useful for the improvement of strains.

• Korean Journal of Microbiology
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• v.50 no.2
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• pp.95-100
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• 2014

Hrq1 is a novel member of RecQ helicase family, found in fungal genomes by bioinformatics analyses. It is most homologous to human RECQL4 and recent genetic and biochemical studies suggested that it may play roles in the maintenance of genome stability. In this study, we investigated yeast two-hybrid interactions between Hrq1 and the yeast genes homologous to the human genes that are known to interact with RECQL4. Among the 11 genes tested, Rad14, a nucleotide excision repair (NER) factor, was found to interact with Hrq1. In addition, pull-down assay with the purified proteins revealed direct protein-protein interaction between Hrq1 and Rad14. The yeast two-hybrid interaction was enhanced by the DNA damage induced by 4-nitroquinoline-1-oxide, which was dependent on the presence of Rad4, a key NER factor. These results suggest that Hrq1 may function in NER through interaction with Rad14.

• Development and Reproduction
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• v.12 no.2
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• pp.117-124
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• 2008

The efficient strategies to cope with unpredictable and/or harmful environmental changes have been developed by every organism in order to ensure its survival and continuity of it's own species. As a results, all living things on earth maintain dynamically internal stability via a process termed 'homeostasis' among physiological parameters despite of external environment changes. Stress is an emotional and physical response to threat homeostasis. Stress may have not only transient but rather permanent effect on the organism; recent evidence clearly show that prenatal stress could organize or imprint permanently physiological systems without any change in genetic codes, a process known as 'epigenetic programming'. In this review, a series of reproduction-associated events occurred in prenatally stressed male rats such as alteration in the structure of sexually dimorphic brain regions, modification of neurotransmitter metabolism, changes in reproductive endocrine status, and finally, disorders of sexual behavior will be introduced. The fetal brain is highly sensitive to prenatal programming and glucocorticoids in particular have powerful brain-programming properties. The chronic hyperactivation of fetal brain by maternal stress-induced glucocorticoid input will provide new program via increasing the neuroplasticities. This 'increased neuroplasticities' will be the basis for the 'increased phenotypic plasticities' rendering the organism's better adaptation to environmental challenges. In conclusion, organism who experienced 'harsh' environment in his fetal life seems to give up a certain portion of reproductive competence to make good chance of survival in his future life by epigenetic (re)programming.

• Biomolecules & Therapeutics
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• v.23 no.2
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• pp.189-194
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• 2015

P450 1A2 is responsible for the metabolism of clinically important drugs and the metabolic activation of environmental chemicals. Genetic variations of P450 1A2 can influence its ability to perform these functions, and thus, this study aimed to characterize the functional significance of three P450 1A2 allelic variants containing nonsynonymous single nucleotide polymorphisms (P450 $1A2^*8$, R456H; $^*15$, P42R; $^*16$, R377Q). Variants containing these SNPs were constructed and the recombinant enzymes were expressed and purified in Escherichia coli. Only the P42R variant displayed the typical CO-binding spectrum indicating a P450 holoenzyme with an expression level of ~ 170 nmol per liter culture, but no P450 spectra were observed for the two other variants. Western blot analysis revealed that the level of expression for the P42R variant was lower than that of the wild type, however the expression of variants R456H and R377Q was not detected. Enzyme kinetic analyses indicated that the P42R mutation in P450 1A2 resulted in significant changes in catalytic activities. The P42R variant displayed an increased catalytic turnover numbers ($k_{cat}$) in both of methoxyresorufin O-demethylation and phenacetin O-deethylation. In the case of phenacetin O-deethylation analysis, the overall catalytic efficiency ($k_{cat}/K_m$) increased up to 2.5 fold with a slight increase of its $K_m$ value. This study indicated that the substitution P42R in the N-terminal proline-rich region of P450 contributed to the improvement of catalytic activity albeit the reduction of P450 structural stability or the decrease of substrate affinity. Characterization of these polymorphisms should be carefully examined in terms of the metabolism of many clinical drugs and environmental chemicals.

• Korean Journal of Veterinary Research
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• v.48 no.4
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• pp.441-449
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• 2008

The genus Lactobacillus is the largest of the genera included in lactic acid bacteria and is associated with mucosal membranes of human and animal. Only a few Lactobacillus plasmid-encoded functions have been discovered and used. In this study, a novel plasmid (pILR091) was isolated from a wild L. reuteri isolated from pig and described the characteristics of its replicons, genetic organization, and relationship with other plasmids. After digestion of the plasmid, pILR091, with SalI, plasmid DNA was cloned into the pQE-30Xa vector and sequenced. The complete sequence was confirmed by the sequencing of PCR products and analyzed with the Genbank database. The isolate copy number and stability were determined by quantitative-PCR. The complete sequence of L. reuteri contained 7,185 nucleotides with 39% G-C content and one cut site by two enzymes, SalI and HindIII. The similar ori sequence of the pC194- rolling circle replication family (TTTATATTGAT) was located 63 bp upstream of the protein replication sequence, ORF 1. Total of five ORFs was identified and the coding sequence represented 4,966 nucleotides (70.4%). ORF1 of pILR091 had a low similarity with the sequence of pTE44. Other ORFs also showed low homology and E-values. The average G-C content of pILR091 was 39%, similar with that of genomic DNA. The copy number of pILR091 was determined at approximately 24 to 25 molecules per genomic DNA. These results suggested that pILR091 might be a good candidate to construct a new vector, which could be used for cloning and expression of foreign genes in lactobacilli.