• Mycobiology
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• v.36 no.2
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• pp.102-105
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• 2008

The acetylcholinesterase (AChE) inhibitor of Yarrowia lipolytica S-3 was maximally produced when it was incubated at $30^{\circ}C$ for 36 h in an optimal medium containing 1% yeast extract, 2% peptone and 2% glucose, with an initial pH 6.0. The final AChE inhibitory activity under these conditions was an $IC_{50}$ value of 64mg/ml. After partial purification of the AChE inhibitor by means of systematic solvent extraction, the final $IC_{50}$ value of the partially purified AChE inhibitor was 0.75 mg/ml. We prepared a test product by using the partially purified AChE inhibitor and then determined its stability for the development of a new antidementia commercial product. The test product was stable at room temperature for 15 weeks.

• Korean Management Science Review
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• v.14 no.1
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• pp.67-76
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• 1997

The most research on facility layout problems ignored the actual shapes of activity spaces and the aisles between activities. In many cases, the research also ignored the actual shape of building where the activities are to be arranged. In this paper, We present a block based layout technique that applies a genetic algorithm to search for a very good facility layout with horizontal aisles. From the extensive experiments for two different cases with respect to the shape of activity space, it was found that the proposed method generated better layouts than the ones obtained by applying Tam's algorithm in all test problems. The proposed algorithm showed about 10% improvement of performance on the average. We determined the best combination of the reproduction rule and the genetic operators with their probabilities for each test problem through the experiment.

• Journal of Genetic Medicine
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• v.5 no.2
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• pp.89-93
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• 2008

"Personalized medicine," the goal of which is to provide better clinical care by applying patient's own genomic information to their health care is a global challenge for the $21^{st}$ century "genomic era." This is especially true in Korea, where provisions for clinical genetic services are inadequate for the existing demand, let alone future demands. Genomics-based knowledge and tools make it possible to approach each patient as a unique biological individual, which has led to a paradigm-shift in medical practice, giving it more of a predictive focus as compared with current treatment oriented approach. With recent advancements in genomics, many genetic tests, such as susceptibility genetic tests, have been developed for both rare single gene diseases and more common multifactorial diseases. Indeed, genetic tests for presymtomatic individuals and genetic tests for drug response have become widely available, and personalized medicine will face the challenge of assisting patients who use such tests to make appropriate and wise use of genetic risk assessment. A major challenge of genomic medicine lies in understanding and communicating disease risk in order to facilitate and support patients and their families in making informed decisions. Establishment of a health care system with provisions for genetic counseling as an integral part of health care service, in addition to genomic literacy of health care providers, is vital to meet this growing challenge. Realization of the promise of personalized medicine in the era of genomics for improvement of health care is dependent on further development of next generation sequencing technology and affordable sequencing test costs. Also necessary will be policy development concerning the ethical, legal and social issues of genomic medicine and an educated and ready medical community with clinical practice guidelines for genetic counseling and genetic testing.

• The Journal of Information Systems
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• v.12 no.2
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• pp.1-20
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• 2003

This paper deals with the application of the genetic algorithm to the technical trading rule of the stock market. MACD(Moving Average Convergence & Divergence) and the Stochastic techniques are widely used technical trading rules in the financial markets. But, it is necessary to determine the parameters of these trading rules in order to use the trading rules. We use the genetic algorithm to obtain the appropriate values of the parameters. We use the daily KOSPI data of eight years during January 1995 and October 2002 as the experimental data. We divide the total experimental period into learning period and testing period. The genetic algorithm determines the values of parameters for the trading rules during the teaming period and we test the performance of the algorithm during the testing period with the determined parameters. Also, we compare the return of the genetic algorithm with the returns of buy-hold strategy and risk-free asset. From the experiment, we can see that the genetic algorithm outperforms the other strategies. Thus, we can conclude that genetic algorithm can be used successfully to the technical trading rule.

• Genomics & Informatics
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• v.8 no.3
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• pp.142-149
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• 2010

In recent years, genome-wide association (GWA) studies have successfully led to many discoveries of genetic variants affecting common complex traits, including height, blood pressure, and diabetes. Although GWA studies have made much progress in finding single nucleotide polymorphisms (SNPs) associated with many complex traits, such SNPs have been shown to explain only a very small proportion of the underlying genetic variance of complex traits. This is partly due to that fact that most current GWA studies have relied on single-marker approaches that identify single genetic factors individually and have limitations in considering the joint effects of multiple genetic factors on complex traits. Joint identification of multiple genetic factors would be more powerful and provide a better prediction of complex traits, since it utilizes combined information across variants. Recently, a new statistical method for joint identification of genetic variants for common complex traits via the elastic-net regularization method was proposed. In this study, we applied this joint identification approach to a large-scale GWA dataset (i.e., 8842 samples and 327,872 SNPs) in order to identify genetic variants of obesity for the Korean population. In addition, in order to test for the biological significance of the jointly identified SNPs, gene ontology and pathway enrichment analyses were further conducted.

• Childhood Kidney Diseases
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• v.28 no.1
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• pp.8-15
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• 2024

With the rapid evolution of diagnostic tools, particularly next-generation sequencing, the identification of genetic diseases, predominantly those with pediatric-onset, has significantly advanced. However, this progress presents challenges that span from selecting appropriate tests to the final interpretation of results. This review examines various genetic testing methodologies, each with specific indications and characteristics, emphasizing the importance of selecting the appropriate genetic test in clinical practice, taking into account factors like detection range, cost, turnaround time, and specificity of the clinical diagnosis. Interpretation of variants has become more challenging, often requiring further validation and significant resource allocation. Laboratories primarily classify variants based on the American College of Medical Genetics and Genomics and the Association for Clinical Genomic Science guidelines, however, this process has limitations. This review underscores the critical role of clinicians in matching patient phenotypes with reported genes/variants and considering additional factors such as variable expressivity, disease pleiotropy, and incomplete penetrance. These considerations should be aligned with specific gene-disease characteristics and segregation results based on an extended pedigree. In conclusion, this review aims to enhance understanding of the complexities of clinical genetic testing, advocating for a multidisciplinary approach to ensure accurate diagnosis and effective management of rare genetic diseases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5464-5488
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• 2019

The multi-population genetic algorithm in multi-target paths coverage has become a top choice for many test engineers. Also, information sharing strategy can improve the efficiency of multi-population genetic algorithm to generate multi-target test data; however, there is still space for some improvements in several aspects, which will affect the effectiveness of covering the target path set. Therefore, a multi-target paths coverage strategy is proposed by improving multi-population genetic algorithm based on individual information sharing among populations. It primarily contains three aspects. Firstly, the behavior of the sub-population covering corresponding target path is improved, so that it can continue to try to cover other sub-paths after covering the current target path, so as to take full advantage of population resources; Secondly, the populations initialized are prioritized according to the matching process, so that those sub-populations with better path coverage rate are executed firstly. Thirdly, for difficultly-covered paths, the individual chromosome features which can cover the difficultly-covered paths are extracted by utilizing the data generated, so as to screen those individuals who can cover the difficultly-covered paths. In the experiments, several benchmark programs were employed to verify the accuracy of the method from different aspects and also compare with similar methods. The experimental results show that it takes less time to cover target paths by our approach than the similar ones, and achieves more efficient test case generation process. Finally, a plug-in prototype is given to implement the approach proposed.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.4
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• pp.53-60
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• 2019

In this study, a method for updating the finite element model of bridges with genetic algorithm using static displacement were presented, and verified this method using field test data for PSC girder bridge. As a field test, static load test and pseudo-static load test were conducted, and updated the finite element model of test bridge using each test data. Finally, evaluated the bridge load carrying capacity with updated model using pseudo-static load test's displacement data. To evaluate the bridge load carrying capacity, KHBDC-LSD, KHBDC and AASHTO LRFD's live load model were used, and compared the each results.

• Korean Journal of Clinical Laboratory Science
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• v.42 no.1
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• pp.22-31
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• 2010

The most common sources of biological trace material which are found in crime scene are the human bloodstains. Reliable identification in the forensic casework is important as it provides crucial insights into crime scene reconstruction and can thus contribute towards solving crimes. Blood-stains are routinely tested in forensic practise using various methods including the leucomalachite green (LMG) test, Kastle-Meyer phenolphthalein test, tetramethylbenzidine test, orthotolidine test, or the luminol chemoluminescence test with the latter cleaning attempts. All these presumptive thus indicative but not identifying tests take advantage of the peroxidase-like activity of the heme unit of the hemoglobin molecule in human blood. Therefore, false-positive results can be caused by the presence of strong oxidants, such as chlorine-containing detergents or by true peroxidases (e.g., from plants). In this study, composition for Gum guaiac was evaluated for the forensic identification of bloodstain and compared with the LMG. The sensitivity and specificity of the composition for Gum guaiac were examined more stable in bloodstain. The positive of Composition for Gum guaiac shown even with the 100,000-fold diluted bloodstain, which was no difference in comparison with LMG test. It was shown that composition for Gum guaiac was very stable to resist boiling for 20 minutes and the effect of bacteria did not affect the genetic analysis as well. The above result of the crime scene investigation, composition for Gum guaiac is easily expected to help identifying bloodstain in the evidences.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.4
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• pp.470-475
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• 2013

The objective of this study was to estimate genetic parameters that are to be used for across-herd genetic evaluations of seed stock pigs at GGP level. Performance data with pedigree information collected from swine breeder farms in Korea were provided by Korea Animal Improvement Association (AIAK). Performance data were composed of final body weights at test days and ultrasound measures of back fat thickness (BF), rib eye area (EMA) and retail cut percentage (RCP). Breeds of swine tested were Landrace, Yorkshire and Duroc. Days to 90 kg body weight (DAYS90) were estimated with linear function of age and ADG calculated from body weights at test days. Ultrasound measures were taken with A-mode ultrasound scanners by trained technicians. Number of performance records after censoring outliers and keeping records pigs only born from year 2000 were of 78,068 Duroc pigs, 101,821 Landrace pigs and 281,421 Yorkshire pigs. Models included contemporary groups defined by the same herd and the same seasons of births of the same year, which was regarded as fixed along with the effect of sex for all traits and body weight at test day as a linear covariate for ultrasound measures. REML estimation was processed with REMLF90 program. Heritability estimates were 0.40, 0.32, 0.21 0.39 for DAYS90, ADG, BF, EMA, RCP, respectively for Duroc population. Respective heritability estimates for Landrace population were 0.43, 0.41, 0.22, and 0.43 and for Yorkshire population were 0.36, 0.38, 0.22, and 0.42. Genetic correlation coefficients of DAYS90 with BF, EMA, or RCP were estimated to be 0.00 to 0.09, -0.15 to -0.25, 0.22 to 0.28, respectively for three breeds populations. Genetic correlation coefficients estimated between BF and EMA was -0.33 to -0.39. Genetic correlation coefficient estimated between BF and RCP was high and negative (-0.78 to -0.85) but the environmental correlation coefficients between these two traits was medium and negative (near -0.35), which describes a highly correlated genetic response to selection on one or the other of these traits. Genetic Trends of all three breeds tend to be towards bigger EMA or greater RCP and shorter DAYS90 especially from generations born after year 2000.