• 한국발생생물학회지:발생과생식
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• 제21권3호
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• pp.229-235
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• 2017

In the field of reproductive medicine, assessment of sperm motility is a key factor for achieving successful artificial insemination, in vitro fertilization, or intracellular sperm injection. In this study, the motility of boar sperms was estimated using real-time imaging via confocal microscopy. To confirm this confocal imaging method, flagellar beats and whiplash-like movement angles were compared between fresh and low-temperature-preserved ($17^{\circ}C$ for 24 h) porcine sperms. Low-temperature preservation reduced the number of flagellar beats from $11.0{\pm}2.3beats/s$ (fresh sperm) to $5.7{\pm}1.8beats/s$ and increased the flagellar bending angle from $19.8^{\circ}{\pm}13.8^{\circ}$ (fresh) to $30.6^{\circ}{\pm}15.6^{\circ}$. These data suggest that sperm activity can be assessed using confocal microscopy. The observed motility patterns could be used to develop a sperm evaluation index and automated confocal microscopic sperm motility analysis techniques.

• Interdisciplinary Bio Central
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• 제6권1호
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• pp.1.1-1.6
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• 2014

A growing body of evidence shows that most psychological traits are polygenic, that is they involve the action of many genes with small effects. However, the study of selection has disproportionately been on one or a few genes and their associated sweep signals (rapid and large changes in frequency). If our goal is to study the evolution of psychological variables, such as intelligence, we need a model that explains the evolution of phenotypes governed by many common genetic variants. This study illustrates simple statistical tools to detect signals of recent polygenic selection: a) ANOVA can be used to reveal significant deviation from random distribution of allele frequencies across racial groups. b) Principal component analysis can be used as a tool for finding a factor that represents the strength of recent selection on a phenotype and the underlying genetic variation. c) Method of correlated vectors: the correlation between genetic frequencies and the average phenotypes of different populations is computed; then, the resulting correlation coefficients are correlated with the corresponding alleles' genome-wide significance. This provides a measure of how selection acted on genes with higher signal to noise ratio. Another related test is that alleles with large frequency differences between populations should have a higher genome-wide significance value than alleles with small frequency differences. This paper fruitfully employs these tools and shows that common genetic variants exhibit subtle frequency shifts and that these shifts predict phenotypic differences across populations.

• 대한산업공학회지
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• 제39권5호
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• pp.361-366
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• 2013

Prediction of process parameters is very important in parameter design. If predictions are fairly accurate, the quality improvement process will be useful to save time and reduce cost. The concept of dual response approach based on response surface methodology has widely been investigated. Dual response approach may take advantages of optimization modeling for finding optimum setting of input factor by separately modeling mean and variance responses. This study proposes an alternative dual response approach based on machine learning techniques instead of statistical analysis tools. A hybrid neural network-genetic algorithm has been proposed for the purpose of parameter design. A neural network is first constructed to model the relationship between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Using empirical process data, process parameters can be predicted without performing real experimentations. A genetic algorithm is then applied to find the optimum settings of input factors, where the neural network is used to evaluate the mean and variance response. A drug formulation example from pharmaceutical industry has been studied to demonstrate the procedures and applicability of the proposed approach.

• Journal of Microbiology and Biotechnology
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• 제4권4호
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• pp.237-244
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• 1994

The vector systems for the expression and secretion of human lipocortin-l (LC1) from Saccharomyces cerevisiae were constructed with GAL10 promoter and the prepro leader sequence of mating factor-$\alpha$1. They were further constructed to contain three different transcription terminators; GAL7 terminator, LCl terminator and a fused form of these two terminators. The expression and secretion levels of LCl were compared to investigate the effect of transcription terminators on the LCl gene expression. For the expression cassettes employing the GAL7 terminator or the terminator of fused form, the expression levels of LCl were measured by scanning the immunoreactive LCl protein bands, and were found to be 0.27 g/l and 0.32 g/l, respectively. The highest expression level of 0.54 g/l was obtained with the expression vector containing the LCl transcription terminator. In all expression cassettes, the majority of LCl proteins expressed were retained intracellularly, indicating a low secretion efficiency of about 5%. The high expression level of LCl was explained by the great content and stability of LCl mRNA transcribed from the LCl terminator-employing vector. The results of this study demonstrate that the LCl transcription terminator functions for the expression of LCl in S. cerevisiae better than the GAL7 terminator.

• 한국해양공학회지
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• 제18권5호
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• pp.29-35
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• 2004

A new approach, referred to as a successive zooming genetic algorithm (SZGA), is proposed for identifying a global solution, using continuous zooming factors for optimization problems. In order to improve the local fine-tuning of the GA, we introduced a new method whereby the search space is zoomed around the design variable with the best fitness per 100 generation, resulting in an improvement of the convergence. Furthermore, the reliability of the optimized solution is determined based on the theory of probability, and the parameter used for the successive zooming method is optimized. With parameter optimization, we can eliminate the time allocated for deciding parameters used in SZGA. To demonstrate the superiority of the proposed theory, we tested for the minimization of a multiple function, as well as simple functions. After testing, we applied the parameter optimization to a truss problem and wicket gate servomotor optimization. Then, the proposed algorithm identifies a more exact optimum value than the standard genetic algorithm.

• 한국정밀공학회지
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• 제22권7호
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• pp.112-121
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• 2005

This paper is concerned with smooth trajectory generation of biped robot which has inverted pendulum type balancing weight. Genetic algorithm is used to generate the trajectory of the leg and balancing weight. Balancing trajectory can be determined by solving the second order differential equation under the condition that the reference ZMP (Zero moment point) is settled. Reference ZMP effect on gait pattern absolutely but the problem is how to determine the reference ZMP. Genetic algorithm can find optimal solution under the high order nonlinear situation. Optimal trajectory is generated when use genetic algorithm which has some genes and a fitness function. In this paper, minimization of balancing joints motion is used for the fitness function and set the weight factor of the two balancing joints at the fitness function. Inverted pendulum type balancing weight is very similar with human and this model can be used fur humanoid robot. Simulation results show ZMP trajectory and the walking experiment made on the real biped robot IWR-IV.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권11호
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• pp.599-609
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• 2000

The new design methodology of a hybrid fuzzy controller by means of the genetic algorithms is presented. First, a hybrid fuzzy controller(HFC) related to the optimal estimation of control parameters is proposed. The control input for the system in the HFC combined PID controller with fuzzy controller is a convex combination of the FLC's output and PID's output by a fuzzy variable, namely, membership function of weighting coefficient. Second, an auto-tuning algorithms utilizing the simplified reasoning method and genetic algorithms is presented to automatically improve the performance of hybrid fuzzy controller. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The proposed HFC is evaluated and discussed to show applicability and superiority with the and of three representative processes.

• Genomics & Informatics
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• 제12권4호
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• pp.236-239
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• 2014

The genetic regulation of glucose and insulin levels might be modified by adiposity. With regard to the genetic factors that are altered by adiposity, a large meta-analysis on the interactions between genetic variants and body mass index with regard to fasting glucose and insulin levels was reported by the Meta-Analyses of Glucose- and Insulin-related trait Consortium (MAGIC), based on European ancestry. Because no replication study has been performed in other ethnic groups, we first examined the link between reported single-nucleotide polymorphisms (SNPs) and fasting glucose and insulin levels in a large Korean cohort (Korean Genome and Epidemiology Study cohort [KoGES], n = 5,814). The MAGIC study reported 7 novel SNPs for fasting glucose levels and 6 novel SNPs for fasting insulin levels. In this study, we attempted to replicate the association of 5 SNPs with fasting glucose levels and 5 SNPs with fasting insulin levels. One SNP (rs2293941) in PDX1 was identified as a significant obesity-modifiable factor in Koreans. Our results indicate that the novel loci that were identified by MAGIC are poorly replicated in other ethnic groups, although we do not know why.

• Genomics & Informatics
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• 제8권3호
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• pp.101-102
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• 2010

During the last decade, large community cohorts have been established by the Korea National Institutes of Health (KNIH), and enormous epidemiological and clinical data have been accumulated. Using these information and samples in the cohorts, KNIH set out to do a large-scale genome-wide association study (GWAS) in 2007, and the Korea Association REsource (KARE) consortium was launched to analyze the data to identify the underlying genetic risk factors of diseases and diverse health indexes, such as blood pressure, obesity, bone density, and blood biochemical traits. The consortium consisted of 6 research divisions, formed by 25 principal investigators in 19 organizations, including 18 universities, 2 institutes, and 1 company. Each division focused on one of the following subjects: the identification of genetic factors, the statistical analysis of gene-gene interactions, the genetic epidemiology of gene-environment interactions, copy number variation, the bioinformatics related to a GWAS, and a GWAS of nutrigenomics. In this special issue, the study results of the KARE consortium are provided as 9 articles. We hope that this special issue might encourage the genomics community to share data and scientists, including clinicians, to analyze the valuable Korean data of KARE.

• 동의생리병리학회지
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• 제19권2호
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• pp.515-519
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• 2005

We hypothesized that the IL10 gene is important candidate in the development of Bell's palsy and specific genotypic and allelic variations should be associated with Bell's palsy in the Korean population. In this study, we assessed the SNP (single-nucleotide polymorphism) of IL10 in patients with Bell's palsy. 62 patients with Bell's palsy were selected from the subjects who visited for the Bell's palsy service of the department of acupuncture & moxibustion, college of Oriental Medicine, Daegu Haany University from May 2002 to May 2003. Pyrosequencing was performed for genetic analyses. There was no statistically significant genotypic distribution difference between control and Bell's palsy group And there was not statistically significant allelic frequency difference between control and Bell's palsy group. In this study the IL10 genotypemight not be the risk factor of Bell's palsy patients in Korean. studies will be necessary for the exact genetic markers. Establishment of more systemic approach and high quality of prospective cohorts will be necessary for the good prediction of genetic markers.