• ETRI Journal
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• 제38권1호
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• pp.206-215
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• 2016

The detection of gene-gene interactions during genetic studies of common human diseases is important, and the technique of multifactor dimensionality reduction (MDR) has been widely applied to this end. However, this technique is not free from the "curse of dimensionality" -that is, it works well for two- or three-way interactions but requires a long execution time and extensive computing resources to detect, for example, a 10-way interaction. Here, we propose a boosting method to reduce MDR execution time. With the use of pre-evaluation measurements, gene sets with low levels of interaction can be removed prior to the application of MDR. Thus, the problem space is decreased and considerable time can be saved in the execution of MDR.

• Journal of Preventive Medicine and Public Health
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• 제40권2호
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• pp.108-113
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• 2007

When conducting large-scale cohort studies, numerous statistical issues arise from the range of study design, data collection, data analysis and interpretation. In genomic cohort studies, these statistical problems become more complicated, which need to be carefully dealt with. Rapid technical advances in genomic studies produce enormous amount of data to be analyzed and traditional statistical methods are no longer sufficient to handle these data. In this paper, we reviewed several important statistical issues that occur frequently in large-scale genomic cohort studies, including measurement error and its relevant correction methods, cost-efficient design strategy for main cohort and validation studies, inflated Type I error, gene-gene and gene-environment interaction and time-varying hazard ratios. It is very important to employ appropriate statistical methods in order to make the best use of valuable cohort data and produce valid and reliable study results.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.623-626
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• 2006

Group of genes controls the functioning of a cell by complex interactions. These interacting gene groups are called Gene Regulatory Networks (GRNs). Two previous data mining approaches, clustering and classification have been used to analyze gene expression data. While these mining tools are useful for determining membership of genes by homology, they don't identify the regulatory relationships among genes found in the same class of molecular actions. Furthermore, we need to understand the mechanism of how genes relate and how they regulate one another. In order to detect regulatory relationships among genes from time-series Microarray data, we propose a novel approach using frequent pattern mining and chain rule. In this approach, we propose a method for transforming gene expression data to make suitable for frequent pattern mining, and detect gene expression patterns applying FP-growth algorithm. And then, we construct gene regulatory network from frequent gene patterns using chain rule. Finally, we validated our proposed method by showing that our experimental results are consistent with published results.

• 자연과학논문집
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• 제9권1호
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• pp.25-29
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• 1997

Glucocorticoid에 의한 항염증 작용의 second messenger로 생각되어지는 annexin superfamily중 하나인 37 kDa의 단백질, lipocortin-1의 작용기작을 이해할 목적으로 in vivo에서 protein-protein interaction을 인식하는 yeast-based genetic assay인 yeast two assay를 통하여 lipocortin-1과 결합하는 단백질 유전자를 분리하여 조사하였다. 이 방법으로 실험을 수행한 결과 분리된 유전자가 human serine proteinase 유전자와 homology가 있는 것으로 밝혀졌다.

• 동의생리병리학회지
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• 제18권5호
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• pp.1426-1436
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• 2004

There have been several reports on the relationship between G protein β3 subunit gene (GNB3), angiotensin converting enzyme gene (ACE), β3-adrenergic receptor gene (ADRB3), and β2-adrenergic receptor gene (ADRB2) genotype and obesity or obesity related disease. The objective of this study was to examine the relationship between the combinations of these four genes' polymorphism and probability of obesity related disease in Korean female subjects. The experimental group was consisted of 85 obese Korean female subjects (body mass index, BMI≥27㎏/㎡). To determine the polymorphism, genomic DNA was isolated, and PCR was performed. Serological examinations (fasting plasma glucose, FPG; aspartate aminotranferase, AST; alanine aminotransferase, ALT; total cholesterol, TC; triglyceride, TG; high density lipoprotein-cholesterol, HDL; low density lipoprotein-choles terol, LDL) were carried by an autoanalyzer and serological methods. BMI, waist circumference (WC), hip circumference and waist hip ratio (WHR) were measured. Consequencely in the analysis with grouping of general genotyping and variant allele carrier/non-carrier, the result was not significantly different within all gene combinations and polymorphic pairings except higher waist circumference in Arg16Arg group of ADRB2 codon16 (P=0.024). And there was no significantly contrast result about age, height, weight, AST and ALT that are index feature of liver and gall bladder disease in polymorphic pairings of gene combinations. However, the statistical analysis of waist-hip ratio and waist circumference that could be recognized as the physical type of obesity showed T-Arg16 pairing carrier in GNB3-ADRB2 codon16 combination had increased WHR and WC significantly (P=0.046 and P=0.015 respectively). Futhermore, the levels of total cholesterol (TC) and low density lipoprotein choresteral (LDL) were significantly lower in C-I pairing of GNB3-ACE combination (P=0.032 and P=0.005). These results suggest that the T-Arg16 pairing carrier in GNB3-ADRB2 codon16 gene might have increased waist circumference and C-I pairing carrier in GNB3-ACE combination have lower possibility of contraction of cardiovascular disease related cholesterol and LDL despite of obese state.

• BMB Reports
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• 제35권6호
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• pp.562-567
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• 2002

In order to find the cellular interaction factors of the Heliothis armigera nuclear polyhedrosis virus capsid protein VP39, a Heliothis armigera cell cDNA library was constructed. Then VP39 was used as bait. The host actin gene was isolated from the cDNA library with the yeast two-hybrid system. This demonstrated that VP39 could interact with its host actin in yeast. In order to corroborate this interaction in vivo, the vp39 gene was fused with the green fluorescent protein gene in plasmid pEGFP39. The fusion protein was expressed in the Hz-AM1 cells under the control of the Autographa californica multiple nucleopolyhedrovirus immediate early gene promoter. The host actin was labeled specifically by the red fluorescence substance, tetramethy rhodamine isothicyanete-phalloidin. Observation under a fluorescence microscopy showed that VP39, which was indicated by green fluorescence, began to appear in the cells 6 h after being transfected with pEGFP39. Red actin cables were also formed in the cytoplasm at the same time. Actin was aggregated in the nucleus 9 h after the transfection. The green and red fluorescence always appeared in the same location of the cells, which demonstrated that VP39 could combine with the host actin. Such a combination would result in the actin skeleton rearrangement.

• 생물정신의학
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• 제20권4호
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• pp.129-135
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• 2013

Aggression can be defined as 'behavior intended to harm another' which can be seen both from humans and animals. However, trying to understand aggression in a simplistic view may make it difficult to develop an integrated approach. So, we tried to explain aggression in a multidisciplinary approach, affected by various factors such as neuroanatomical structures, neurotransmitter, genes, and sex hormone. Parallel with animal models, human aggression can be understood with two phenomena, offensive aggression and defensive aggression. Neurobiological model of aggression give a chance to explain aggression with an imbalance between prefrontal regulatory influences and hyper-reactivity of the subcortical areas involved in affective evaluation, finally in an aspect of brain organization. Serotonin and GABA usually inhibit aggression and norepinephrine while glutamate and dopamine precipitate aggressive behavior. As there is no one gene which has been identified as a cause of aggression, functions between gene to gene interaction and gene to environment interaction are being magnified. Contributions of sex hormone to aggression, especially molecular biologic interaction of testosterone and regulation of estrogen receptor have been emphasized during the research on aggression. This multidisciplinary approach on aggression with types, neurochemical bases, and animal models can bring integrated interpretation on aggression.

• Journal of the Korean Data and Information Science Society
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• 제20권1호
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• pp.171-178
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• 2009

제한된 분할방법은 어떤 개체의 표현형을 가장 많이 설명할 수 있는 multilocus 유전자형들의 분할된 그룹을 찾는 것이며 연속형 데이터에 적합하다. 또한 이 방법은 인간의 여러 질병에 영향을 주는 유전자를 찾는 방법으로 주로 이용된다. 그러나 본 연구에서는 제한된 분할 방법을 인간의 질병뿐만 아니라 가축의 경제형질에도 적용할 수 있는 것을 보이기 위해 한우의 여러 경제형질인 등심단면적, 도체중과 일당증체량에 영향을 주는 유전자를 규명해 보았다. 그 결과 모든 경제형질에 영향을 주는 유전자로는 SNP (19_1)$^*$SNP (28_2)의 상호작용이 가장 좋은 SNP로 선정되었다. 따라서 이 유전자 SNP (19_1)$^*$SNP (28_2)가 한우의 경제형질에 가장 많은 영향을 준다는 것을 규명하였으며 제한된 분할 방법이 가축의 경제형질에도 적용할 수 있다는 것을 보였다.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 추계 학술발표회 논문집
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• pp.31-36
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• 2005

An identification and characterization of susceptibility genes for common complex multifactorial diseases is a challengeable task, in which the effect of single genetic variation will be likely dependent on other genetic variations(gene-gene interaction) and environmental factors (gene-environment interaction). To address is issue, the multifactor dimensionality reduction (MDR) has been proposed and implemented by Ritchie et al. (2001), Moore et al. (2002), Hahn et al.(2003) and Ritchie et al. (2003). With MDR, multilocus genotypes effectively reduce the dimension of genotype predictors from n to one, which improves the identification of polymorphism combinations associated with disease risk. However, MDR cannot handle missing observations appropriately, in which missing observation is treated as an additional genotype category. This approach may suffer from a sparseness problem since when high-order interactions are considered, an additional missing category would make the contingency table cells more sparse. We propose a new MDR approach with minimum loss of sample sizes by considering missing data over all possible multifactor classes. We evaluate the proposed MDR by using the prediction errors and cross validation consistency.

• Communications for Statistical Applications and Methods
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• 제29권1호
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• pp.65-83
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• 2022

Although various statistical methods have been developed to map time-dependent genetic factors, most identified genetic variants can explain only a small portion of the estimated genetic variation in longitudinal traits. Gene-gene and gene-time/environment interactions are known to be important putative sources of the missing heritability. However, mapping epistatic gene-gene interactions is extremely difficult due to the very large parameter spaces for models containing such interactions. In this paper, we develop a Gaussian process (GP) based nonparametric Bayesian variable selection method for longitudinal data. It maps multiple genetic markers without restricting to pairwise interactions. Rather than modeling each main and interaction term explicitly, the GP model measures the importance of each marker, regardless of whether it is mostly due to a main effect or some interaction effect(s), via an unspecified function. To improve the flexibility of the GP model, we propose a novel grid-based method for the within-subject dependence structure. The proposed method can accurately approximate complex covariance structures. The dimension of the covariance matrix depends only on the number of fixed grid points although each subject may have different numbers of measurements at different time points. The deviance information criterion (DIC) and the Bayesian predictive information criterion (BPIC) are proposed for selecting an optimal number of grid points. To efficiently draw posterior samples, we combine a hybrid Monte Carlo method with a partially collapsed Gibbs (PCG) sampler. We apply the proposed GP model to a mouse dataset on age-related body weight.