• Genomics & Informatics
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• v.4 no.2
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• pp.51-56
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• 2006

In planning a genetic association study, it is necessary to determine the number of samples to be collected for the study in order to achieve sufficient power to detect the hypothesized effect. The case-control design is increasingly used for genetic association studies due to the simplicity of its design. We review the methods for the sample size and power calculations in case-control genetic association studies between a marker locus and a disease phenotype.

• Animal cells and systems
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• v.8 no.1
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• pp.41-47
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• 2004

The kallikrein-kinin system affects regulation of blood pressure, and genes encoding for the components of this system have been considered as good candidates for hypertension. To evaluate the relationship between genetic polymorphisms of candidate genes involved in this system and hypertension, we performed case-control studies using genetic markers in Korean normotensives and hypertensives, respectively. By association study, there was a marginal association with hypertension in AA genotype distribution of A1789G polymorphism in the hKLK1 gene (P=0.0754). Thus, this genetic polymorphism may weakly contribute to the susceptibility to hypertension in Koreans. We also observed that significant linkage disequilibrium exists among three polymorphic sites in the hKLK1 gene studied, suggesting that the three genetic polymorph isms can be useful as genetic markers in clinical association studies. Further studies using larger sample sizes and more genetic markers will be needed to clarify genetic influence of kallikrein-kinin system for hypertension.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.2
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• pp.183-191
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• 2019

Objective: The purpose of this study was to compare intended and actual yearly genetic gains for milk production and conformation traits and to investigate the simple selection criterion practiced among milk production and conformation traits during the last two decades in Japan. Learning how to utilize the information on intended and actual genetic gains during the last two decades into the genomic era is vital. Methods: Genetic superiority for each trait for four paths of selection (sires to breed bulls [SB], sires to breed cows [SC], dams to breed bulls [DB], and dams to breed cows [DC]) was estimated. Actual practiced simple selection criteria were investigated among milk production and conformation traits and relative emphasis on milk production and conformation traits was compared. Results: Selection differentials in milk production traits were greater than those of conformation traits in all four paths of selection. Realized yearly genetic gain was less than that intended for milk production traits. Actual annual genetic gain for conformation traits was equivalent to or greater than intended. Retrospective selection weights of milk production and conformation traits were 0.73:0.27 and 0.56:0.44 for intended and realized genetic gains, respectively. Conclusion: Selection was aimed more toward increasing genetic gain in milk production than toward conformation traits over the past two decades in Japan. In contrast, actual annual genetic gain for conformation traits was equivalent to or greater than intended. Balanced selection between milk production and conformation traits tended to be favored during actual selection. Each of four paths of selection (SB, SC, DB, and DC) has played an individual and important role. With shortening generation interval in the genomic era, a young sire arises before the completion of sire's daughters' milk production records. How to integrate these four paths of selection in the genomic era is vital.

• Korean Journal of Biological Psychiatry
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• v.3 no.1
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• pp.14-21
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• 1996

Molecular genetic approaches contribute to the understanding of the underlying genetic mechanism for schizophrenia. Currently genetic evidence rests on molecular genetic methods. However, the result are contradictory and somewhat confusing due to genetic heterogeneity, incomplete penetrance, misspecification of genetic model. It is expected that molecular genetics could provide key answers to the genetic cause of schizophrenia. The purpose of this article is to call attention of the readers to heterogeneity, linkage, association, basic molecular genetic methods and genetic markers and to the need far further research. It is the author's hope thai continuous research on the molecular genetics con provide clinicians with better understanding of the schizophrenia.

• Genomics & Informatics
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• v.14 no.4
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• pp.187-195
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• 2016

In genetic association studies with high-dimensional genomic data, multiple group testing procedures are often required in order to identify disease/trait-related genes or genetic regions, where multiple genetic sites or variants are located within the same gene or genetic region. However, statistical testing procedures based on an individual test suffer from multiple testing issues such as the control of family-wise error rate and dependent tests. Moreover, detecting only a few of genes associated with a phenotype outcome among tens of thousands of genes is of main interest in genetic association studies. In this reason regularization procedures, where a phenotype outcome regresses on all genomic markers and then regression coefficients are estimated based on a penalized likelihood, have been considered as a good alternative approach to analysis of high-dimensional genomic data. But, selection performance of regularization procedures has been rarely compared with that of statistical group testing procedures. In this article, we performed extensive simulation studies where commonly used group testing procedures such as principal component analysis, Hotelling's $T^2$ test, and permutation test are compared with group lasso (least absolute selection and shrinkage operator) in terms of true positive selection. Also, we applied all methods considered in simulation studies to identify genes associated with ovarian cancer from over 20,000 genetic sites generated from Illumina Infinium HumanMethylation27K Beadchip. We found a big discrepancy of selected genes between multiple group testing procedures and group lasso.

• Journal of Korean Association for Spatial Structures
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• v.3 no.4 s.10
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• pp.59-67
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• 2003

Genetic algorithm is one of the best ways to solve a discrete variable optimization problem. Genetic algorithm tends to thrive in an environment in which the search space is uneven and has many hills and valleys. In this study, genetic algorithm is used for solving the design problem of gable structure. The design problem of frame structure has some special features(complicate design space, many nonlinear constrants, integer design variables, termination conditions, special information for frame members, etc.), and these features must be considered in the formulation of optimization problem and the application of genetic algorithm. So, 'FRAME operator', a new genetic operator for solving the frame optimization problem effectively, is developed and applied to the design problem of gable structure. This example shows that the new opreator has the possibility to be an effective frame design operator and genetic algorithm is suitable for the frame optimization problem.

• Journal of Korean Association for Spatial Structures
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• v.2 no.3 s.5
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• pp.93-102
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• 2002

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithms. The algorithm can perform both shape and topology optimum designs of trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithms. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithms were verified by applying the algorithm to optimum design examples

• Journal of Genetic Medicine
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• v.4 no.1
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• pp.15-21
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• 2007

Hereditary syndromes cause approximately 5 to 10% of overall cancer cases. Cancer related with genetic syndromes are found elsewhere, including stomach, breast, colorectum, ovary, brain and so on. Because hereditary cancers are due to germline mutations, these patients have unique clinical features distinct from sporadic cancer. Generally these features include (i) early age-of onset of cancer, (ii) frequent association with synchronous or metachronous tumors, (iii) frequent bilateral involvement in paired organs (iv) frequent association with other site tumors or characteristic clinical manifestation specific to each genetic syndrome. Due to these differences, the management strategy for patients with hereditary cancer is quite different from that for sporadic cancer. Additionally, there are important screening and surveillance implications for family members. Genetic counselling is prerequisite to these families for risk assessment by pedigree analysis, and guidance to clinical or genetic testing. The genes responsible for these syndromes has recently identified, as a result, genetic testing has become important determining factor in clinical decisions.

• International Journal of Human Ecology
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• v.11 no.2
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• pp.15-23
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• 2010

This study explored genetic and environmental contributions to optimism, depressive symptoms, and the association between the two using a genetically informative sample from the Nonshared Environment and Adolescent Development project (NEAD: D. Reiss; J. M. Neiderhiser; E. M. Hetherington; & R. Plomin, 2000. At Time 1 of the longitudinal NEAD study, the sample consisted of 720 samesex twins and sibling pairs from two parent families. The study used parent, adolescent, and observer ratings of depressive symptoms as well as adolescent ratings of optimism. The results revealed that genetic influences explained approximately half of the variability in optimism and depressive symptoms. Nonshared environmental influences also substantially contributed to optimism and depressive symptoms. Bivariate genetic analyses (which partitioned the covariance between optimism and depressive symptoms into genetic and environmental components) indicated that genetic influences accounted for a moderate percentage of the association.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.1
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• pp.1-7
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• 2017

Objective: Three genome-wide association studies (GWAS) and a meta-analysis of GWAS were conducted to explore the genetic mechanisms underlying variation in pig teat number. Methods: We performed three GWAS and a meta-analysis for teat number on three pig populations, including a White Duroc${\times}$Erhualian $F_2$ resource population (n = 1,743), a Chinese Erhualian pig population (n = 320) and a Chinese Sutai pig population (n = 383). Results: We detected 24 single nucleotide polymorphisms (SNPs) that surpassed the genome-wide significant level on Sus Scrofa chromosomes (SSC) 1, 7, and 12 in the $F_2$ resource population, corresponding to four loci for pig teat number. We highlighted vertnin (VRTN) and lysine demethylase 6B (KDM6B) as two interesting candidate genes at the loci on SSC7 and SSC12. No significant associated SNPs were identified in the meta-analysis of GWAS. Conclusion: The results verified the complex genetic architecture of pig teat number. The causative variants for teat number may be different in the three populations