• Communications for Statistical Applications and Methods
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• 제17권5호
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• pp.667-678
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• 2010

인간의 유전자 상호작용을 분석하기 위해 제시된 다중인자 차원축소방법은 연속형자료에는 적용할 수 없다. 그래서 이를 보완한 CART 알고리즘을 활용한 확장된 다중인자 차원축소방법이 제안되었다. 하지만 CART 알고리즘을 활용한 확장된 다중인자 차원축소방법의 검정력이 밝혀지지 않았다. 따라서 본 연구에서는 모의실험을 통하여 CART 알고리즘을 활용한 확장된 다중인자 차원축소방법의 우수한 검정력을 평가하고, 확인된 검정력을 바탕으로 실제 한우 데이터에 적용하여 한우의 경제형질에 영향을 주는 우수 유전자조합을 규명하였다.

• Communications for Statistical Applications and Methods
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• 제18권4호
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• pp.413-422
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• 2011

유전학에서 유전자 상호작용효과 규명을 위한 방법으로 비모수적인 방법인 Multifactor Dimensionality Reduction(MDR) 방법이 제안되어 현재까지 사용되고 있다. MDR 방법은 이분형 자료에 적합한 방법으로 연속형 자료에는 적용할 수 없는 단점이 있다. 이러한 한계를 극복하기 위해서 Dummy MDR(D-MDR) 방법 그리고 SVM을 활용한 MDR(SVM MDR) 방법 등이 제안 되었다. 본 논문에서는 연속형 자료에 적용 가능한 SVM MDR 방법과 D-MDR 방법을 비교하고, 실제 한우 데이터에 두 방법에 적용한다. 그리고 각 방법의 적용결과를 바탕으로 한우의 종합경제형질에 영향을 주는 유전자 상호작용 조합을 규명한다. 그리고 마지막으로 기존의 SVM MDR 방법과 D-MDR 방법의 장단점 비교를 통해서 추후 새로운 연구방향을 제시한다.

• 대한가정학회지
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• 제44권8호
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• pp.33-45
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• 2006

The main purpose of the current research was to examine the married women's "Family Multifactor Leadership Questionnaire I" which is a new strategy for developing the strength of family. The survey was conducted with three hundred married women who have a child or children attending elementary school, based upon relationship. The main results of the present study are as following. First, the level of the married women's "Family Multifactor Leadership Questionnaire I" tended to be relatively high and they were good at charismatic leadership among sub-dimension of "Family Multifactor Leadership Questionnaire I". Moreover, internal and external controllability and social support turned out to be most influential background variables. Second, the score for the strengths of family that is recognized by the married women appeared to be more than average. It seemed that internal and external controllability, social support, and monthly gross family income were the most influential variables. Indeed, the result of stepwise regression analysis showed that transformational leadership made a comparatively high contribution to the married women's strength of family. Therefore, it is important to keep in mind that married women's leadership development is a main source of maintaining healthy family.

• The Journal of Asian Finance, Economics and Business
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• 제8권12호
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• pp.75-83
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• 2021

Variation in demand, natural resource availability, and technological advancement within a country are the main reasons for necessitating export and import activities between nations. Accordingly, this paper aims to analyze the effect of economic openness on Multifactor Productivity (MFP) in selected Asian countries (Vietnam, Thailand, The Philippines, Indonesia, Cambodia, China, Japan, Malaysia, South Korea, and Singapore) based on data for the period 1990-2018. The analysis conducted in the study employed the panel ARDL approach based on the estimation by Pooled Mean Group (PMG), Mean Group (MG), and Dynamic Fixed Effect (DFE). The Hausman test conducted indicates that the PMG estimation is better than that of MG and DFE since it has a higher variability value than the significance value. The results revealed that economic openness is able to elicit significant and positive effects on short-term and long-term MFP growth. In addition, the study established that other variable, such as the number of schooling years, are also able to produce a positive and significant effect on MFP growth in the long term. Since economic openness can impact MFP growth, every country should thus increase its export activities through more capital and worker inputs that will stimulate greater production.

• Communications for Statistical Applications and Methods
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• 제15권2호
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• pp.265-271
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• 2008

It is commonly believed that diseases of human or economic traits of livestock are caused not by single genes acting alone, but multiple genes interacting with one another. This issue is difficult due to the limitations of parametric-statistic methods of gene effects. So we introduce multifactor-dimensionality reduction(MDR) as a methods for reducing the dimensionality of multilocus information. The MDR method is nonparametric (i. e., no hypothesis about the value of a statistical parameter is made), model free (i. e., it assumes no particular inheritance model) and is directly applicable to case-control studies. Application of the MDR method revealed the best model with an interaction effect between the SNPs, SNP1 and SNP3, while only one main effect of SNP1 was statistically significant for LMA (p < 0.01) under a general linear mixed model.

• 응용통계연구
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• 제22권2호
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• pp.435-442
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• 2009

통계모형의 상호작용 효과를 분석하기 위해 비모수적인 방법인 다중인자 차원 축소(MDR) 방법을 사용해왔다. MDR 방법은 사례-대조 데이터에만 적용 할 수 있다. 본 논문에서는 연속형 데이터에도 적용 할 수 있는 더미(dummy) 변수를 활용한 MDR방법을 소개한다. 아울러 이를 통해 한우의 주요 경제형질인 등심단면적 (longissimus muscle dorsi area: LMA), 도체중(carcass cold weight: CWT), 일당증체량(average daily gain: ADC)에 영향을 주는 우수 유전자 단일염기다형성(SNP)을 규명한다.

• 응용통계연구
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• 제23권4호
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• pp.693-703
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• 2010

대개 인간의 질병과 관련된 유전자나 가축의 경제적인 특성과 관련된 유전자는 주로 상호작용으로 일어난다. 유전자의 상호작용을 찾기 위한 방법으로 다양한 방법들이 제시되었다. 본 논문에서는 유전자의 상호작용 효과를 규명하기 위해 개발된 확장된 MDR방법(E-MDR)과 더미변수를 활용한 MDR방법(D-MDR), 대규모 유전자들 중에서 주요 유전자 조합을 선별하는 SNPHarvester방법을 비교하여 인간의 질병이 아닌 한우의 경제적인 특성에 적용하여 우수한 유전자 조합을 선별하고 우수 유전자형을 밝힌다.

• Journal of the Korean Data and Information Science Society
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• 제22권6호
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• pp.1257-1264
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• 2011

Delirium is a neuropsychiatric disorder accompanying symptoms of hallucination, drowsiness, and tremors. It has high occurrence rates among elders, heart disease patients, and burn patients. It is a medical emergency associated with increased morbidity and mortality rates. That s why early detection and prevention of delirium ar significantly important. And This mental illness like delirium occurred by complex interaction between risk factors. In this paper, we identify risk factors and interactions between these factors for delirium using multi-factor dimensionality reduction (MDR) method.

• Genomics & Informatics
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• 제16권4호
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• pp.37.1-37.3
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• 2018

Gene-gene interaction is a key factor for explaining missing heritability. Many methods have been proposed to identify gene-gene interactions. Multifactor dimensionality reduction (MDR) is a well-known method for the detection of gene-gene interactions by reduction from genotypes of single-nucleotide polymorphism combinations to a binary variable with a value of high risk or low risk. This method has been widely expanded to own a specific objective. Among those expansions, fuzzy-MDR uses the fuzzy set theory for the membership of high risk or low risk and increases the detection rates of gene-gene interactions. Fuzzy-MDR is expanded by a maximum likelihood estimator as a new membership function in empirical fuzzy MDR (EFMDR). However, EFMDR is relatively slow, because it is implemented by R script language. Therefore, in this study, we implemented EFMDR using RCPP ($c^{{+}{+}}$ package) for faster executions. Our implementation for faster EFMDR, called EMMDR-Fast, is about 800 times faster than EFMDR written by R script only.

• Asian-Australasian Journal of Animal Sciences
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• 제21권6호
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• pp.784-788
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• 2008

Studies to detect genes responsible for economic traits in farm animals have been performed using parametric linear models. A non-parametric, model-free approach using the 'expanded multifactor-dimensionality reduction (MDR) method' considering high dimensionalities of interaction effects between multiple single nucleotide polymorphisms (SNPs), was applied to identify interaction effects of SNPs responsible for carcass traits in a Hanwoo beef cattle population. Data were obtained from the Hanwoo Improvement Center, National Agricultural Cooperation Federation, Korea, and comprised 299 steers from 16 paternal half-sib proven sires that were delivered in Namwon or Daegwanryong livestock testing stations between spring of 2002 and fall of 2003. For each steer at approximately 722 days of age, the Longssimus dorsi muscle area (LMA) was measured after slaughter. Three functional SNPs (19_1, 18_4, 28_2) near the microsatellite marker ILSTS035 on BTA6, around which the QTL for meat quality were previously detected, were assessed. Application of the expanded MDR method revealed the best model with an interaction effect between the SNPs 19_1 and 28_2, while only one main effect of SNP19_1 was statistically significant for LMA (p<0.01) under a general linear mixed model. Our results suggest that the expanded MDR method better identifies interaction effects between multiple genes that are related to polygenic traits, and that the method is an alternative to the current model choices to find associations of multiple functional SNPs and/or their interaction effects with economic traits in livestock populations.