• Genomics & Informatics
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• v.18 no.1
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• pp.11.1-11.3
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• 2020

In genome-wide association studies, pathway-based analysis has been widely performed to enhance interpretation of single-nucleotide polymorphism association results. We proposed a novel method of hierarchical structural component model (HisCoM) for pathway analysis of common variants (HisCoM for pathway analysis of common variants [HisCoM-PCA]) which was used to identify pathways associated with traits. HisCoM-PCA is based on principal component analysis (PCA) for dimensional reduction of single nucleotide polymorphisms in each gene, and the HisCoM for pathway analysis. In this study, we developed a HisCoM-PCA software for the hierarchical pathway analysis of common variants. HisCoM-PCA software has several features. Various principle component scores selection criteria in PCA step can be specified by users who want to summarize common variants at each gene-level by different threshold values. In addition, multiple public pathway databases and customized pathway information can be used to perform pathway analysis. We expect that HisCoM-PCA software will be useful for users to perform powerful pathway analysis.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1155-1163
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• 2004

Extracellular signal-regulated kinase (ERK) signaling pathway is one of the mitogen-activated protein kinase (MAPK) signal transduction pathways. This pathway is known as pivotal in many signaling networks that govern proliferation, differentiation and cell survival. The ERK signaling pathway comprises positive and negative feedback loops, depending on whether the terminal kinase stimulates or inhibits the activation of the initial level. In this paper, we attempt to model the ERK pathway by considering both of the positive and negative feedback mechanisms based on Michaelis-Menten kinetics. In addition, we propose a fraction ratio model based on the mass action law. We first develop a mathematical model of the ERK pathway with fraction ratios. Secondly, we analyze the dynamical properties of the fraction ratio model based on simulation studies. Furthermore, we propose a concept of an inhibitor, catalyst, and substrate (ICS) controller which regulates the inhibitor, catalyst, and substrate concentrations of the ERK signal transduction pathway. The ICS controller can be designed through dynamical analysis of the ERK signaling transduction pathway within limited concentration ranges.

• The Korean Journal of Physiology and Pharmacology
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• v.20 no.4
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• pp.367-378
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• 2016

Recently, it was reported that the role of mitochondria-reactive oxygen species (ROS) generating pathway in cisplatin-induced apoptosis is remarkable. Since a variety of molecules are involved in the pathway, a comprehensive approach to delineate the biological interactions of the molecules is required. However, quantitative modeling of the mitochondria-ROS generating pathway based on experiment and systemic analysis using the model have not been attempted so far. Thus, we conducted experiments to measure the concentration changes of critical molecules associated with mitochondrial apoptosis in both human mesothelioma H2052 and their ${\rho}^0$ cells lacking mitochondrial DNA (mtDNA). Based on the experiments, a novel mathematical model that can represent the essential dynamics of the mitochondrial apoptotic pathway induced by cisplatin was developed. The kinetic parameter values of the mathematical model were estimated from the experimental data. Then, we have investigated the dynamical properties of this model and predicted the apoptosis levels for various concentrations of cisplatin beyond the range of experiments. From parametric perturbation analysis, we further found that apoptosis will reach its saturation level beyond a certain critical cisplatin concentration.

• Genomics & Informatics
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• v.6 no.4
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• pp.202-209
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• 2008

Biological pathways are known as collections of knowledge of certain biological processes. Although knowledge about a pathway is quite significant to further analysis, it covers only tiny portion of genes that exists. In this paper, we suggest a model to extend each individual pathway using a microarray expression data based on the known knowledge about the pathway. We take the Rosetta compendium dataset to extend pathways of Saccharomyces cerevisiae obtained from KEGG (Kyoto Encyclopedia of genes and genomes) database. Before applying our model, we verify the underlying assumption that microarray data reflect the interactive knowledge from pathway, and we evaluate our scoring system by introducing performance function. In the last step, we validate proposed candidates with the help of another type of biological information. We introduced a pathway extending model using its intrinsic structure and microarray expression data. The model provides the suitable candidate genes for each single biological pathway to extend it.

• Genomics & Informatics
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• v.17 no.4
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• pp.45.1-45.3
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• 2019

To identify pathways associated with survival phenotypes using gene expression data, we recently proposed the hierarchical structural component model for pathway analysis of gene expression data (HisCoM-PAGE) method. The HisCoM-PAGE software can consider hierarchical structural relationships between genes and pathways and analyze multiple pathways simultaneously. It can be applied to various types of gene expression data, such as microarray data or RNA sequencing data. We expect that the HisCoM-PAGE software will make our method more easily accessible to researchers who want to perform pathway analysis for survival times.

• Genomics & Informatics
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• v.3 no.1
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• pp.30-34
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• 2005

Microarray technology makes it possible to measure the expressions of tens of thousands of genes simultaneously under various experimental conditions. Identifying differentially expressed genes in each single experimental condition is one of the most common first steps in microarray gene expression data analysis. Reasonable choices of thresholds for determining differentially expressed genes are used for the next-stap-analysis with suitable statistical significances. We present a supervised model for identifying DEGs using pathway information based on the global connectivity structure. Pathway information can be regarded as a collection of biological knowledge, thus we are trying to determine the optimal threshold so that the consequential connectivity structure can be the most compatible with the existing pathway information. The significant feature of our model is that it uses established knowledge as a reference to determine the direction of analyzing microarray dataset. In the most of previous work, only intrinsic information in the miroarray is used for the identifying DEGs. We hope that our proposed method could contribute to construct biologically meaningful structure from microarray datasets.

• The Korean Journal of Applied Statistics
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• v.23 no.4
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• pp.705-713
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• 2010

Predicting survival from microarray data is not easy due to the problem of high dimensionality of data and the existence of censored observations. Also the limitation of individual gene analysis causes the shift of focus to the level of gene sets with functionally related genes. For developing a survival prediction model based on pathway information, the methods for selecting a supergene using principal component analysis and testing its significance for each pathway are discussed. Besides, the performance of gene filtering is compared.

• Journal of Environmental Impact Assessment
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• v.14 no.5
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• pp.291-303
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• 2005

Impact pathway analysis(IPA) is a bottom-up approach to estimates health and environmental risks from emissions of classical pollutants (eg. $PM_{10}$, $SO_2$, $NO_x$ and CO). The model starts from the emission rates of facility, calculates the yearly mean concentrations of pollutants at the ground level using atmospheric dispersion models. After this, proper epidemiological exposure-response functions are applied to determine the impact on the receptors. Finally the methodology can monetise the calculated physical impact on the basis of selected economic evaluation. The aim of this study is to evaluate an external cost of virtual point source in Suwon area using IPA. The results shows minor modification of local input data can make it possible to apply the model to Suwon area.

• Journal of Radiation Protection and Research
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• v.16 no.2
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• pp.67-74
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• 1991

Parameter uncertainty and sensitivity of KFOOD model for calculating the ingestion dose via terrestrial food-chain pathway was analyzed with using Monte-Carlo approach. For the rice ingestion pathway, estimated values from KFOOD code were very conservative. Most sensitive input parameters in model were deposition velocities and soil-to-plant transfer coefficient of radionuclides.

• Proceedings of the Korean Society of Applied Pharmacology
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• 1998.11a
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• pp.158-158
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• 1998

The non-mevalonate pathway is a newly discovered isoprenoid biosynthetic pathway in some bacteria, cyanobacteria, algae and plants. Because isoprenoid metabolites (ubiquinone, menaquinone, undecaprenol) are essential for bacterial growth, this pathway may represent a novel target for antibacterial agents. Antibiotics with a unique mechanism of action are needed to combat the risk of antibiotic resistance that is a current worldwide problem. In order to study this pathway as viable target, it was necessary to verify use of the pathway in our model system, the bacterium Bacillus subtilis. Incubation experiments with [6,6-$^2$H$_2$]-D-glucose and [l-$^2$H$_3$]-deoxy-D-xylulose were conducted to provide labeled menaquinone-7 (MK -7), the most abundant isoprenoid in B. subtilis. $^2$H-NMR analysis of the MK-7 revealed labeling patterns that strongly support utilization of the non-mevalonate pathway. Another approach to study the pathway is by structure activity relationships of proposed inhibitors of the pathway. Fosmidomycin is a phosphonic acid with antibacterial activity known to inhibit isoprenoid biosynthesis in susceptible bacteria and may act by inhibiting the non-mevalonate pathway. Fosmidomycin and an N-methyl analog were synthesized and tested for antibacterial activity. Fosmidomycin was active against Escherichia coli and B. subtilis, while N-formyl-N-methyl-3-amino-propylphosphonic acid was inactive.