• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2003.11a
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• pp.428-431
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• 2003

In this paper, distances between elements are optimized for low sidelobe level (SLL) microstrip patch array using Genetic Algorithms. Genetic Algorithms are "global" numerical-optimization methods, it's advantages are very simple coding and fast optimization. This paper show how to optimize the maximum SLL using Genetic Algorithms. In the results, although mutual coupling is neglected, it's maximum SLL is 3.5 dB lower than Uniformly Spaced Array(distance=$0.5{\lambda}$).

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.270-272
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• 2006

In this paper, we discuss optimal design of Fuzzy Polynomial Neural Networks by means of Genetic Algorithms(GAs) using symbolic coding for non-linear data. One of the major subject of genetic algorithms is representation of chromosomes. The proposed model optimized by the means genetic algorithms which used symbolic code to represent chromosomes. The proposed gFPNN used a triangle and a Gaussian-like membership function in premise part of rules and design the consequent structure by constant and regression polynomial (linear, quadratic and modified quadratic) function between input and output variables. The performance of the proposed model is quantified through experimentation that exploits standard data already used in fuzzy modeling. These results reveal superiority of the proposed networks over the existing fuzzy and neural models.

• Journal of Genetic Medicine
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• v.12 no.1
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• pp.6-11
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• 2015

Intellectual disability (ID) is the most common disability among people under the age of 20 years. In the absence of obvious non-genetic causes of ID, the majority of cases of severe ID are thought to have a genetic cause. The advent of technologies such as array comparative genomic hybridization, single nucleotide polymorphism genotyping arrays, and massively parallel sequencing has shown that de novo copy number variations and single nucleotide variations affecting coding regions are major causes of severe ID. This article reviews the genetic causes of ID along with diagnostic approaches for this disability.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.71.2-71
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• 2001

This paper deals with nonlinear system modelling using neural network and genetic algorithm. Application of neural network to control and identification is actively studied because of their approximating ability of nonlinear function. It is important to design the neural network with optimal structure for minimum error and fast response time. Genetic algorithm is getting more popular nowadays because of their simplicity and robustness. In this paper, We optimize neural network structure using genetic algorithm. The genetic algorithm uses binary coding for neural network structure and search for optimal neural network structure of minimum error and response time. Through extensive simulation, Optimal neural network structure is shown to be effective for ...

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.153-156
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• 2001

Fuzzy controllers also show good performance In case of the systems being nonlinear and difficult to solve. But these fuzzy controllers have problems which have to decide suitable rules and membership functions. In general we decide those using the heuristic methods or the experience of experts. Therefore, many researchers have applied genetic algorithms to make fuzzy rule automatically. In this paper, we suggest a new coding method and a new crossover method to maintain the good fuzzy rule base and the shape of membership

• Proceedings of the Korean Society of Sericultural Science Conference
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• 2003.04a
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• pp.40-40
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• 2003

Recombinant plasmids harboring heterologous genes coding enhanced green fluorescent protein (EGFP) and erythropoietin (EPO) were transfected and expressed in Drosophila melanogaster S2 cells. Stably transformed cell populations expressing EGFP or monkey EPO were isolated after 4 weeks of selection with hygromycin B. (omitted)

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2633-2635
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• 2000

In this paper, a new DNA coding method, namely modified DNA coding method based on the biological DNA and the evolution mechanism of genetic algorithm. In order to evaluate the propose algorithms, for an example, they are applied to the fuzzy control of parallel double inverted pendulum system. Simulation result show the method is effective in finding the fuzzy control rules and is more excellent than conventional methods in control the system.

• Molecules and Cells
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• v.42 no.5
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• pp.379-385
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• 2019

Non-coding RNAs (ncRNAs) comprise various RNA species, including small ncRNAs and long ncRNAs (lncRNAs). ncRNAs regulate various cellular processes, including transcription and translation of target messenger RNAs. Recent studies also indicate that ncRNAs affect organismal aging and conversely aging influences ncRNA levels. In this review, we discuss our current understanding of the roles of ncRNAs in aging and longevity, focusing on recent advances using the roundworm Caenorhabditis elegans. Expression of various ncRNAs, including microRNA (miRNA), tRNA-derived small RNA (tsRNA), ribosomal RNA (rRNA), PIWI-interacting RNA (piRNA), circular RNA (circRNA), and lncRNA, is altered during aging in C. elegans. Genetic modulation of specific ncRNAs affects longevity and aging rates by modulating established aging-regulating protein factors. Because many aging-regulating mechanisms in C. elegans are evolutionarily conserved, these studies will provide key information regarding how ncRNAs modulate aging and lifespan in complex organisms, including mammals.

• Journal of Microbiology and Biotechnology
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• v.14 no.6
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• pp.1163-1169
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• 2004

An unstructured mathematical model is presented for lactic acid fermentation based on the energy balance. The proposed model reflects the energy metabolic state and then predicts the cell growth, lactic acid production, and glucose consumption rates by relating the above rates with the energy metabolic rate. Fermentation experiments were conducted under various initial lactic acid concentrations of 0, 30, 50, 70, and 90 g/l. Also, a genetic algorithm was used for further optimization of the model parameters and included the operations of coding, initialization, hybridization, mutation, decoding, fitness calculation, selection, and reproduction exerted on individuals (or chromosomes) in a population. The simulation results showed a good fit between the model prediction and the experimental data. The genetic algorithm proved to be useful for model parameter optimization, suggesting wider applications in the field of biological engineering.

• Journal of Microbiology and Biotechnology
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• v.1 no.4
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• pp.266-273
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• 1991

Hirudin, a 65-amino acid protein isolated from the salivary gland of the bloodsucking leech, Hirudo medicinalis, is a potent thrombin-specific inhibitor and blocks the thrombin-mediated conversion of fibrinogen to fibrin in clot formation. We have studied the gene expression and secretion of hirudin in yeast. Saccharomyces cerevisiae. A gene coding for hirudin was synthesized based on the amino acid sequence and cloned into a yeast expression vector $YEG{\alpha}-1$ containing the ${\alpha}-mating$ factor pre-pro leader sequence and galactose-inducible promoter, GALl0. Recombinant S. cerevisiae was found to secrete biologically active hirudin into the extracellular medium. The secreted recombinant hirudin was recovered from the culture medium and purified with ultrafiltration and reverse phase high performance liquid chromatography. Approximately 1 mg of hirudin per liter was produced under suboptimal culture conditions and brought to about 90% purity in two steps of purification.