• 예술인문사회 융합 멀티미디어 논문지
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• 제8권4호
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• pp.251-258
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• 2018

수학과 컴퓨터 과학 분야에서 최적화 문제란 가능한 모든 해 중에서 가장 좋은 해를 찾는 문제이다. 유전 알고리즘에서 최적화 문제의 어려운 정도는 상위의 측면에서 설명될 수 있다. 생물학에서 상위는 유전자의 표현형이 하나 혹은 그 이상의 유전자에 의해 억제되는 것을 의미하지만 진화 알고리즘에서는 유전자들 사이의 상호작용을 의미한다. 본 논문에서는 상위와 유전 알고리즘이 최적 해를 찾는 시간 사이의 상관관계를 실험적으로 확인하였다. Shannon의 정보 이론에 근거해 상위를 수치화하는 프레임워크를 사용하여 다양한 문제(One-Max, Royal Road, NK-Landscape)의 상위를 비교하였고, 그 결과 상위가 커짐에 따라 문제가 어려워져 최적 해를 찾기 어려운 경향이 있음을 확인하였다. 성능은 주어진 세대 안에 최적 해를 찾는 경우 최적 해를 찾는 데까지 걸린 세대 수로 비교하였고, 최적 해를 찾지 못하는 경우 최적 해의 적합도에 대한 주어진 세대 동안 찾은 적합도가 가장 높은 해의 적합도 비율로 비교하였다.

• BMB Reports
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• 제42권9호
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• pp.617-622
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• 2009

We investigated the genetic associations of ischemic stroke by identifying epistasis of its heterogeneous subtypes such as small vessel occlusion (SVO) and large artery atherosclerosis (LAA). Epistasis was analyzed with 24 genes in 207 controls and 271 patients (SVO = 110, LAA = 95) using multifactor dimensionality reduction and entropy decomposition. The multifactor dimensionality reduction analysis with any of 1- to 4-locus models showed no significant association with LAA (P > 0.05). The analysis of SVO, however, revealed a significant association in the best 3-locus model with P10L of TGF-$\beta{1}$, C1013T of SPP1, and R485K of F5 (testing balanced accuracy = 63.17%, P < 0.05). Subsequent entropy analysis also revealed that such heterogeneity was present and quite a large entropy was estimated among the 3 loci for SVO (5.43%), but only a relatively small entropy was estimated for LAA (1.81%). This suggests that the synergistic epistasis model might contribute specifically to the pathogenetsis of SVO, which implies a different etiopathogenesis of the ischemic stroke subtypes.

• Genomics & Informatics
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• 제12권4호
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• pp.216-224
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• 2014

Gastritis is a common but a serious disease with a potential risk of developing carcinoma. Helicobacter pylori infection is reported as the most common cause of gastritis, but other genetic and genomic factors exist, especially single-nucleotide polymorphisms (SNPs). Association studies between SNPs and gastritis disease are important, but results on epistatic interactions from multiple SNPs are rarely found in previous genome-wide association (GWA) studies. In this study, we performed computational GWA case-control studies for gastritis in Korea Associated Resource (KARE) data. By transforming the resulting SNP epistasis network into a gene-gene epistasis network, we also identified potential gene-gene interaction factors that affect the susceptibility to gastritis.

• Asian-Australasian Journal of Animal Sciences
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• 제25권11호
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• pp.1511-1514
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• 2012

Epistasis that may explain a large portion of the phenotypic variation for complex economic traits of animals has been ignored in many genetic association studies. A Baysian method was introduced to draw inferences about multilocus genotypic effects based on their marginal posterior distributions by a Gibbs sampler. A simulation study was conducted to provide statistical powers under various unbalanced designs by using this method. Data were simulated by combined designs of number of loci, within genotype variance, and sample size in unbalanced designs with or without null combined genotype cells. Mean empirical statistical power was estimated for testing posterior mean estimate of combined genotype effect. A practical example for obtaining empirical statistical power estimates with a given sample size was provided under unbalanced designs. The empirical statistical powers would be useful for determining an optimal design when interactive associations of multiple loci with complex phenotypes were examined.

• 한국정보과학회논문지:소프트웨어및응용
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• 제33권4호
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• pp.440-448
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• 2006

자기 조직화 신경망 (SOM: Self-Organizing Map)은 자율 학습 신경망으로 사전 지식이 존재하지 않는 자료에 존재하는 구조적 관계성을 보전하는데 이용된다. 자기 조직화 신경망은 벡터 양자화, 조합 최적화, 패턴 인식과 같은 복잡한 문제 해결을 위한 연구에 많이 이용되어 왔다. 이 논문에서는 좀더 효율적인 유전 알고리즘을 얻기 위한 스키마 변환 도구로서 자기 조직화 신경망을 이용하는 새로운 사용법에 대해서 제안한다. 즉, 각 자식해는 탐색 공간에서 좀더 바람직한 모양을 가지는 동질의 인공 신경망으로 변환된다. 이 변환으로 인해 강한 상위(epistasis)를 가지는 유전자들은 염색체 상에서 서로 인접하게 되는 것이다. 실험 결과는 기존 결과에 비해서 주목할만한 성능 개선이 있음을 보여준다.

• 한국연초학회지
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• 제14권2호
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• pp.116-125
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• 1992

This experiment was conducted to examine characteristics of agronomic characters and estimate of gene effect for several mutant characters. The genetic populations were derived from cross between 83H-5 and Hicks. There were significant difference for plant height, stlk height, leaf shape and bacterial wilt disease index except leaf number, leaf length, and what is more, F3 variance is more than Bl and B2 generation from cross 83H-5 X Hicks. Gene actions for stalk height and bacterial wilt disease were estimated by 3-parameter, and by 6- parameter model for all characters except above two characters but stalk height and bacterial wilt disease index are not significant in the additive and dominance effects. Dominant$\times$dominant epitasis for plant height, dominant and dominant$\times$dominant epistasis for leaf length, additive and additive$\times$additive and dominant$\times$dominant epistasis for leaf width, and additive and additive$\times$dominant epistasis for days to flower were appeared significant in gene action.

• 환경생물
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• 제26권4호
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• pp.377-384
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• 2008

A cell is the product of a long period of evolution and can be represented as an optimized system (homeostasis). Stimuli from the outside environment are received by sensory apparatus on the surface of the cell and transferred through complicated pathways and eventually regulate gene expression. These signals affect cell physiology, growth, and development, and the interaction among genes in the signal transduction pathway is a critical part of the regulation. In this study, the interactions of deletion mutants and overexpression of the extracopies of the genes were used to understand their relationships to each other. Also, green fluorescent protein (GFP reporter gene) was fused to the regulatory genes to elucidate their interactions. Cooverexpression of the two genes in extracopy plasmids suggested that patS acts at the downstream of hetR in the regulatory network. The experiments using gfp fusion in different genetic background cells also indicated the epistasis relationships between the two genes. A model describing the regulatory network that controls cell development is presented.

• 한국지능시스템학회논문지
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• 제15권6호
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• pp.661-667
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• 2005

본 논문에서는 서열순서화문제를 위한 새로운 혼합형 유전알고리즘을 제안한다. 제안된 유전알고리즘에서는 보로노이양자 화교차를 교차연산자로 사용하고 경로보전 3-최적화를 지역탐색 휴리스틱으로 사용한다. 보로노이양자화교차는 주어진 문제 인스턴스의 상위 정보를 이용하는 교차연산자이다. 이것은 원래 순회판매원문제를 위해서 제안된 교차연산자이기 때문에 서열순서화문제에 적용하기 위해서는 상당한 변형을 필요로 한다. 본 연구에서는 서열순서화문제에 맞도록 보로노이양자화교차를 적절히 변형하고, 변형된 보로노이양자화교차에서 필요로 하는 가능해생성알고리즘, 선행관계사이클분해알고리즘, 유전자거리지정방법 등을 개발하였다. TSPLIB와 ZIB-MP-Testdata로부터 얻어진 서열순서화문제 인스턴스들에 대한 실험결과, 제안된 유전알고리즘이 비교된 다른 유전알고리즘들에 비해서 더 안정적이고 성능이 우수한 것으로 나타났다.

• 전기학회논문지
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• 제57권9호
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• pp.1636-1641
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• 2008

In this study, we introduce a new approach to Parallel Genetic Algorithms (PGA) which combines AHFCGA with crossover operator. As to crossover operators, we use three types of the crossover operators such as modified simple crossover(MSX), arithmetic crossover(AX), and Unimodal Normal Distribution Crossover(UNDX) for real coding. The AHFC model is given as an extended and adaptive version of HFC for parameter optimization. The migration topology of AHFC is composed of sub-populations(demes), the admission threshold levels, and admission buffer for the deme of each threshold level through succesive evolution process. In particular, UNDX is mean-centric crossover operator using multiple parents, and generates offsprings obeying a normal distribution around the center of parents. By using test functions having multimodality and/or epistasis, which are commonly used in the study of function parameter optimization, Experimental results show that AHFCGA can produce more preferable output performance result when compared to HFCGA and RCGA.

• Asian-Australasian Journal of Animal Sciences
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• 제22권1호
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• pp.124-130
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• 2009

Estimating genetic interaction effects in animal genomics would be one of the most challenging studies because the phenotypic variation for economically important traits might be largely explained by interaction effects among multiple nucleotide sequence variants under various environmental exposures. Genetic improvement of economic animals would be expected by understanding multi-locus genetic interaction effects associated with economic traits. Most analyses in animal breeding and genetics, however, have excluded the possibility of genetic interaction effects in their analytical models. This review discusses a historical estimation of the genetic interaction and difficulties in analyzing the interaction effects. Furthermore, two recently developed methods for assessing genetic interactions are introduced to animal genomics. One is the restricted partition method, as a nonparametric grouping-based approach, that iteratively utilizes grouping of genotypes with the smallest difference into a new group, and the other is the Bayesian method that draws inferences about the genetic interaction effects based on their marginal posterior distributions and attains the marginalization of the joint posterior distribution through Gibbs sampling as a Markov chain Monte Carlo. Further developing appropriate and efficient methods for assessing genetic interactions would be urgent to achieve accurate understanding of genetic architecture for complex traits of economic animals.