• BMB Reports
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• v.43 no.12
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• pp.836-841
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• 2010

In the era of personal genomics, predicting the individual response to drug-treatment is a challenge of biomedical research. The aim of this study was to validate whether interaction information between genetic and transcriptional signatures are promising features to predict a drug response. Because drug resistance/susceptibilities result from the complex associations of genetic and transcriptional activities, we predicted the inter-relationships between genetic and transcriptional signatures. With this concept, captured genetic polymorphisms and transcriptional profiles were prepared in cancer samples. By splitting ninety-nine samples into a trial set (n = 30) and a test set (n = 69), the outperformance of relationship-focused model (0.84 of area under the curve in trial set, P = $2.90{\times}10^{-4}$) was presented in the trial set and validated in the test set, respectively. The prediction results of modeling show that considering the relationships between genetic and transcriptional features is an effective approach to determine outcome predictions of drug-treatment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.450-453
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• 1997

There are many studies about optimization using genetic algorithm and desirability function. It's very important to find the optimal value of something like response surface or regression model. In this study I ind~cate the problem using the old type desirability function, and suggest the new type desirabhty functton that can fix the problem better, and simulate the model. Then I'll suggest the form of desirability function to find the optimum value of response surfaces which are made by mean and standard deviation using genetic algorithm and new type desirability function.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.3
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• pp.164-175
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• 2017

Dual response surface optimization (DRSO) attempts to optimize mean and variability of a process response variable using a response surface methodology. In general, mean and variability of the response variable are often in conflict. In such a case, the process engineer need to understand the tradeoffs between the mean and variability in order to obtain a satisfactory solution. Recently, a Posterior preference articulation approach to DRSO (P-DRSO) has been proposed. P-DRSO generates a number of non-dominated solutions and allows the process engineer to select the most preferred solution. By observing the non-dominated solutions, the DM can explore and better understand the trade-offs between the mean and variability. However, the non-dominated solutions generated by the existing P-DRSO is often incomprehensive and unevenly distributed which limits the practicability of the method. In this regard, we propose a modified P-DRSO using multiple objective genetic algorithms. The proposed method has an advantage in that it generates comprehensive and evenly distributed non-dominated solutions.

• Geomechanics and Engineering
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• v.15 no.4
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• pp.937-945
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• 2018

A probabilistic study of a reinforced earth wall in a frictional soil using the surface response methodology (RSM) is presented. A deterministic model based on numerical simulations is used (Abdelouhab et al. 2011, 2012b) and the serviceability limit state (SLS) is considered in the analysis. The model computes the maximum horizontal displacement of the wall. The response surface methodology is utilized for the assessment of the Hasofer-Lind reliability index and is optimized by the use of a genetic algorithm. The soil friction angle and the unit weight are considered as random variables while studying the SLS. The assumption of non-normal distribution for the random variables has an important effect on the reliability index for the practical range of values of the wall horizontal displacement.

• Journal of electromagnetic engineering and science
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• v.4 no.3
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• pp.102-106
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• 2004

A novel Genetic Algorithm(GA)-based method is suggested to transform a coupling matrix to another, without the procedure of Matrix Rotation. This can remove tedious work like pivoting and deciding rotation angles needed for each of the iterations. The error function for the GA is simply formed and used as part of error minimization for obtaining the solution. An 8th order dual-mode elliptic integral function response filter is taken as an example to validate the present method.

• International Journal of Industrial Entomology and Biomaterials
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• v.47 no.2
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• pp.99-114
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• 2023

Patanga japonica Bolívar, 1898 (Orthoptera: Acrididae) is listed as a climate-sensitive indicator species in South Korea and is called southern group of insects in that the main distributional range is southern region of South Korea and Asian continent. In South Korea, thus, the species was distributed mainly in southern region of South Korea including southward a remote Jeju Island, but recently the species has often been detected in mid to northern region of South Korea, implying northward range expansion in response to climate change. Understanding the characteristics of the changes in genetic diversity during range expansion in response to climate change could be a foundation for the understanding of future biodiversity. Thus, in this study, we attempted to understand the changing pattern of the genetic diversity of the P. japonica in newly expanded regions. For the purpose of study, we collected 125 individuals from seven localities throughout South Korea including two newly distributed regions (Pyeongtaek and Yeongwol at ~37° N). These were sequenced for a segment of mitochondrial cytochrome oxidase subunit I (COI) and analyzed for genetic diversity, haplotype frequency, and population genetic structure among populations. Interestingly, northward range expansion accompanied only haplotypes, which are most abundant in the core populations, providing a significant reduction in haplotype diversity, compared to other populations. Moreover, genetic diversity was still lower in the expanded regions, but no genetic isolation was detected. These results suggest that further longer time would take to reach to the comparable genetic diversity of preexisting populations in the expanded regions. Probably, availability of qualified habitats at the newly expanded region could be pivotal for successful northward range expansion in response to climate change.

• Journal of Sericultural and Entomological Science
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• v.36 no.2
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• pp.115-118
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• 1994

Differences of feeding response of 280 silkworm genetic stocks and 71 breeding lines to MP-O artificial diet and the mode of the inheritance were investigated. Feeding response to MP-O diet varied markedly between the silkworm varieties, and the non-normally distributed curve for the response was observed. From the genetic analysis, the high feeding response to MP-O diet was recessive to the low feeding response. Therefore it is considered that the high feeding response of the newly hatched silkwrom larvae to MP-O diet is controlled by a recessive gene.

• 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 ...

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.3
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• pp.299-303
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• 2012

Inbreeding is the mating of relatives that produce progeny having more homozygous alleles than non-inbred animals. Inbreeding increases numbers of recessive alleles, which is often associated with decreased performance known as inbreeding depression. The magnitude of inbreeding depression depends on the level of inbreeding in the animal. Level of inbreeding is expressed by the inbreeding coefficient. One breeding goal in livestock is uniform productivity while maintaining acceptable inbreeding levels, especially keeping inbreeding less than 20%. However, in closed herds without the introduction of new genetic sources high levels of inbreeding over time are unavoidable. One method that increases selection response and minimizes inbreeding is selection of individuals by weighting estimated breeding values with average relationships among individuals. Optimum genetic contribution theory (OGC) uses relationships among individuals as weighting factors. The algorithm is as follows: i) Identify the individual having the best EBV; ii) Calculate average relationships ($\bar{r_j}$) between selected and candidates; iii) Select the individual having the best EBV adjusted for average relationships using the weighting factor k, $EBV^*=EBV_j(1-k\bar{{r}_j})$ Repeat process until the number of individuals selected equals number required. The objective of this study was to compare simulated results based on OGC selection under different conditions over 30 generations. Individuals (n = 110) were generated for the base population with pseudo random numbers of N~ (0, 3), ten were assumed male, and the remainder female. Each male was mated to ten females, and every female was assumed to have 5 progeny resulting in 500 individuals in the following generation. Results showed the OGC algorithm effectively controlled inbreeding and maintained consistent increases in selection response. Difference in breeding values between selection with OGC algorithm and by EBV only was 8%, however, rate of inbreeding was controlled by 47% after 20 generation. These results indicate that the OGC algorithm can be used effectively in long-term selection programs.

• The Korean Journal of Physiology and Pharmacology
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• v.2 no.1
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• pp.101-108
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• 1998

We investigated the effect of ${\alpha}-subunit$ of the stimulatory GTP-binding protein ($G{\alpha}_s$) gene mutation on the expression of the thyrotropin-releasing hormone (TRH) receptor (TRH-R) gene in GH3 cells and in growth hormone (GH)-secreting adenomas of acromegalic patients. In the presence of cyclohexicmide, forskolin and isobutylmethylxanthine, cholera toxin, and GH-releasing hormone (GHRH) decreased rat TRH-R (rTRH-R) gene expression by about 39%, 43.7%, and 46.7%, respectively. Transient expression of a vector expressing mutant-type $G{\alpha}_s$ decreased the rTRH-R gene expression by about 50% at 24 h of transfection, whereas a wild-type $G{\alpha}_s$ expression vector did not. The transcript of human TRH-R (hTRH-R) gene was detected in 6 of 8 (75%) tumors. Three of them (50%) showed the paradoxical GH response to TRH and the other three patients did not show the response. The relative expression of hTRH-R mRNA in the tumors from patients with the paradoxical response of GH to TRH did not differ from that in the tumors from patients without the paradoxical response. Direct PCR sequencing of $G{\alpha}_s$ gene disclosed a mutant allele and a normal allele only at codon 201 in 4 of 8 tumors. The paradoxical response to TRH was observed in 2 of 4 patients without the mutation, and 2 of 4 patients with the mutation. The hTRH-R gene expression of pituitaty adenomsa did not differ between the tumors without the mutation and those with mutation. The present study suggests that the expression of TRH-R gene is not likely to be a main determinant for the paradoxical response of GH to TRH, and that $G{\alpha}_s$ mutation may suppress the gene expression of TRH-R in GH-secreting adenoma. However, a certain predisposing factor(s) may play an important role in determining the expression of TRH-R.