• Communications for Statistical Applications and Methods
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• 제27권5호
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• pp.535-546
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• 2020

In genetic association studies, pleiotropy is a phenomenon where a variant or a genetic region affects multiple traits or diseases. There have been many studies identifying cross-phenotype genetic associations. But, most of statistical approaches for detection of pleiotropy are based on individual tests where a single variant association with multiple traits is tested one at a time. These approaches fail to account for relations among correlated variants. Recently, multivariate regularization methods have been proposed to detect pleiotropy in analysis of high-dimensional genomic data. However, they suffer a problem of tuning parameter selection, which often results in either too many false positives or too small true positives. In this article, we applied selection probability to multivariate regularization methods in order to identify pleiotropic variants associated with multiple phenotypes. Selection probability was applied to individual elastic-net, unified elastic-net and multi-response elastic-net regularization methods. In simulation studies, selection performance of three multivariate regularization methods was evaluated when the total number of phenotypes, the number of phenotypes associated with a variant, and correlations among phenotypes are different. We also applied the regularization methods to a wild bean dataset consisting of 169,028 variants and 17 phenotypes.

• 정보보호학회논문지
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• 제30권3호
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• pp.357-367
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• 2020

2018년 시만텍 보고서에 따르면, 모바일 환경에서 변종 악성 앱은 전년도 대비 54% 증가하였고, 매일 24,000개의 악성 앱이 차단되고 있다. 최근 연구에서는 기존 악성 앱 분석 기술의 사용 한계를 파악하고, 신·변종 악성 앱을 탐지하기 위하여 기계학습을 통한 악성 앱 탐지 기법이 연구되고 있다. 하지만, 기계학습을 적용하는 경우에도 악성 앱의 특성을 적절하게 선택하여 학습하지 못하면 올바른 결과를 보일 수 없다. 본 연구에서는 신·변종 악성 앱의 특성을 찾아낼 수 있도록 개선된 특성 선택 방법을 적용하여 학습 모델의 정확도를 최고 98%까지 확인할 수 있었다. 향후 연구를 통하여 정밀도, 재현율 등 특정 지표의 향상을 목표로 할 수 있다.

• Journal of Microbiology
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• 제37권3호
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• pp.180-184
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• 1999

hybridoma cells producing IgM anti-pneuococcal 6B polysaccharide antibodies were induced to switch to IgG-producing cells in vitro by treating with acridine orange. Treating 0.5 $\mu\textrm{g}$/ml of acridine orange for 24 hours generated maximal number of variant cells. The maximal isotype switch frequency was 3${\times}$10-5, which is about 30-fold higher than the frequency of spontaneous switching. Resulting IgG-producing variants were enriched by sib selection and ELISA spot assay. Two IgG3-producing variant cells were finally cloned by limiting dilution. The variant cells produced similar amounts of antibodies as their parental cells did. The two switched antibodies had similar reactivity to pneumococcal 6B polysaccharide. When compared to their parental IgM antibodies, the switched IgG3 than that of IgM antibody. The antibodies will be useful as essential tools for comparative study of the role of heavy chain isotypes in protection against Streptococcus pneumoniae.

• Asian Pacific Journal of Cancer Prevention
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• 제16권18호
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• pp.8177-8186
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• 2016

The present study was aimed at determining the effects of alkylating and oxidative stress inducing agents on a newly identified variant of DNA polymerase beta ($pol{\beta}{\Delta}_{208-304}$) specific for ovarian cancer. $Pol{\beta}{\Delta}_{208-304}$ has a deletion of exons 11-13 which lie in the catalytic part of enzyme. We compared the effect of these chemicals on HeLa cells and HeLa cells stably transfected with this variant cloned into in pcDNAI/neo vector by MTT, colony forming and apoptosis assays. $Pol{\beta}{\Delta}_{208-304}$ cells exhibited greater sensitivity to an alkylating agent and less sensitivity towards $H_2O_2$ and UV when compared with HeLa cells alone. It has been shown that cell death in $Pol{\beta}{\Delta}_{208-304}$ transfected HeLa cells is mediated by the caspase 9 cascade. Exon 11 has nucleotidyl selection activity, while exons 12 and 13 have dNTP selection activity. Hence deletion of this part may affect polymerizing activity although single strand binding and double strand binding activity may remain same. The lack of this part may adversely affect catalytic activity of DNA polymerase beta so that the variant may act as a dominant negative mutant. This would represent clinical significance if translated into a clinical setting because resistance to radiation or chemotherapy during the relapse of the disease could be potentially overcome by this approach.

• International Journal of Computer Science & Network Security
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• 제21권2호
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• pp.9-13
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• 2021

Type 2 diabetes mellitus (T2D) is a complex diabetes disease that is caused by high blood sugar, insulin resistance, and a relative lack of insulin. Many studies are trying to predict variant genes that causes this disease by using a sample disease model. In this paper we predict diabetic and normal persons by using fisher score feature selection, chi-2 feature selection and Logistic Regression supervised learning algorithm with best accuracy of 90.23%.

• ETRI Journal
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• 제41권5호
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• pp.574-584
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• 2019

A new Mirai variant found recently was equipped with a dynamic update ability, which increases the level of difficulty for DDoS mitigation. Continuous development of 5G technology and an increasing number of Internet of Things (IoT) devices connected to the network pose serious threats to cyber security. Therefore, researchers have tried to develop better DDoS mitigation systems. However, the majority of the existing models provide centralized solutions either by deploying the system with additional servers at the host site, on the cloud, or at third party locations, which may cause latency. Since Internet service providers (ISP) are links between the internet and users, deploying the defense system within the ISP domain is the panacea for delivering an efficient solution. To cope with the dynamic nature of the new DDoS attacks, we utilized an unsupervised artificial neural network to develop a hierarchical two-layered self-organizing map equipped with a twofold feature selection for DDoS mitigation within the ISP domain.

• 한국통신학회논문지
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• 제34권2B호
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• pp.130-142
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• 2009

본 논문에서는 기존의 TCP 변종들을 바탕으로 종단 간의 경로 상에서 나타나는 네트워크 특성에 가장 적응이 잘 이루어진 변종의 알고리즘을 선택하는 TCP의 자동 적응 프레임워크를 제안한다. 프로토콜 선택의 문제가 중요한 이유는 모든 네트워크 환경에 적합한 단일 버전의 프로토콜이 존재하지 않기 때문이며, 이것은 각 네트워크 마다 TCP의 성능 저하 원인이 서로 다르기 때문이다. 이러한 판단 및 프로토콜의 적응이 가능하게 하기 위해 본 논문에서는 기존에 연구되어 왔던 여러 가지 네트워크 측정 기법들과 TCP 변종들을 하나로 합치는 과정을 거쳤으며, 여기에 각 TCP들의 성능 정보들을 제공하여 세션 중간에 적절한 전송 알고리즘을 선택하여 사용할 수 있도록 하였다. 시뮬레이션 실험을 통해 우리는 종단 간으로 여러 환경 하에서 높은 성능을 이끌어낼 수 있다는 것을 보였으며, 제안한 방법이 지금까지 연구되어온 여러 TCP 변종들이 실제로 적절하게 활용될 수 있도록 하는데 중요한 역할을 할 것으로 판단한다.

• 미생물학회지
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• 제50권1호
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• pp.1-7
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• 2014

생명체에서 비천연 아미노산을 단백질의 특정 위치에 삽입하는 방법으로 orthogonal suppressor tRNA와 여기에 비천연 아미노산을 특이적으로 결합시킬 수 있는 유전자 변형된 aminoacyl-tRNA synthetase (ARS)가 활용되고 있다. 이 기술개발을 위해서는 돌연변이를 유발한 ARS library로부터 비천연 아미노산만을 특이적으로 결합시킬 수 있는 변형된 ARS를 탐색하기 위한 선별시스템이 필요하다. 본 논문에서는 대장균에서 작용하는 2단계로 구성된 새로운 선별시스템을 개발하였다. 먼저 양성선별 시스템은 27번 잔기를 amber 코돈으로 치환한 Chloramphenicol acetyl transferase 유전자로 구성되어 있으며, 이유전자의 amber suppression에 의해 chloramphenicol 배지에서 생존함에 따라 활성을 나타내는 ARS를 최고 $9.0{\times}10^5$배로 농축할 수 있었다. 반면 음성선별 시스템은 대장균의 Topoisomerase II의 기능을 억제하는 단백질을 암호화하는 control of cell death B (ccdB) 유전자의 N-말단 앞에 3개의 amber 코돈을 삽입하여 제작하였다. 이 음성선별 시스템을 가진 대장균에 orthogonal pair인 Saccharomyces cerevisiae tyrosyl-tRNA synthetase (Scc TyrRS)와 amber suppressor tRNA를 형질전환하면 amber suppression으로 CcdB가 발현되어 대장균의 성장이 억제되는 것을 확인하였으며, 천연 아미노산에 대한 특이성을 가진 ARS를 효과적으로 제거하는 것을 관찰하였다. 따라서, 양성선별 및 음성선별 시스템을 순차적으로 거침으로써 무작위적으로 아미노산에 대한 특이성을 변형시킨 ARS 라이브러리로부터 비천연 아미노산을 suppressor tRNA에 특이적으로 결합하는 유전자 변형 ARS를 탐색하는데 유용하게 사용될 수 있을 것이다.

• ETRI Journal
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• 제33권2호
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• pp.210-218
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• 2011

Battiti's mutual information feature selector (MIFS) and its variant algorithms are used for many classification applications. Since they ignore feature synergy, MIFS and its variants may cause a big bias when features are combined to cooperate together. Besides, MIFS and its variants estimate feature redundancy regardless of the corresponding classification task. In this paper, we propose an automated greedy feature selection algorithm called conditional mutual information-based feature selection (CMIFS). Based on the link between interaction information and conditional mutual information, CMIFS takes account of both redundancy and synergy interactions of features and identifies discriminative features. In addition, CMIFS combines feature redundancy evaluation with classification tasks. It can decrease the probability of mistaking important features as redundant features in searching process. The experimental results show that CMIFS can achieve higher best-classification-accuracy than MIFS and its variants, with the same or less (nearly 50%) number of features.

• Asian-Australasian Journal of Animal Sciences
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• 제33권4호
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• pp.539-546
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• 2020

Objective: The Jeju native pig (JNP) found on the Jeju Island of Korea is a unique black pig known for high-quality meat. To investigate the genetic uniqueness of JNP, we analyzed the selection signature of the JNP in comparison to commercial pigs such as Berkshire and Yorkshire pigs. Methods: We surveyed the genetic diversity to identify the genetic stability of the JNP, using the linkage disequilibrium method. A selective sweep of the JNP was performed to identify the selection signatures. To do so, the population differentiation measure, Weir-Cockerham's F_st was utilized. This statistic directly measures the population differentiation at the variant level. Additionally, we investigated the gene ontologies (GOs) and genetic features. Results: Compared to the Berkshire and Yorkshire pigs, the JNP had lower genetic diversity in terms of linkage disequilibrium decays. We summarized the selection signatures of the JNP as GO. In the JNP and Berkshire pigs, the most enriched GO terms were epithelium development and neuron-related. Considering the JNP and Yorkshire pigs, cellular response to oxygen-containing compound and generation of neurons were the most enriched GO. Conclusion: The selection signatures of the JNP were identified through the population differentiation statistic. The genes with possible selection signatures are expected to play a role in JNP's unique pork quality.