• Genomics & Informatics
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• v.10 no.4
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• pp.256-262
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• 2012

Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene ($G{\times}G$) interactions. However, the biological interpretation of $G{\times}G$ interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified $G{\times}G$ interactions. The proposed network graph analysis consists of three steps. The first step is for performing $G{\times}G$ interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified $G{\times}G$ interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform $G{\times}G$ interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified $G{\times}G$ interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of $G{\times}G$ interactions.

• Molecules and Cells
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• v.44 no.8
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• pp.602-612
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• 2021

DNA methylation is an important epigenetic mechanism affecting genome structure, gene regulation, and the silencing of transposable elements. Cell- and tissue-specific methylation patterns are critical for differentiation and development in eukaryotes. Dynamic spatiotemporal methylation data in these cells or tissues is, therefore, of great interest. However, the construction of bisulfite sequencing libraries can be challenging if the starting material is limited or the genome size is small, such as in Arabidopsis. Here, we describe detailed methods for the purification of Arabidopsis embryos at all stages, and the construction of comprehensive bisulfite libraries from small quantities of input. We constructed bisulfite libraries by releasing embryos from intact seeds, using a different approach for each developmental stage, and manually picking single-embryo with microcapillaries. From these libraries, reliable Arabidopsis methylome data were collected allowing, on average, 11-fold coverage of the genome using as few as five globular, heart, and torpedo embryos as raw input material without the need for DNA purification step. On the other hand, purified DNA from as few as eight bending torpedo embryos or a single mature embryo is sufficient for library construction when RNase A is treated before DNA extraction. This method can be broadly applied to cells from different tissues or cells from other model organisms. Methylome construction can be achieved using a minimal amount of input material using our method; thereby, it has the potential to increase our understanding of dynamic spatiotemporal methylation patterns in model organisms.

• Journal of The Korean Association For Science Education
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• v.12 no.3
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• pp.35-47
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• 1992

The purpose of this study was to develop a data base system for the information on science education research and development. As a part of this study, a data base program was developed on the Macintosh SE using the 4th Dimension from ACI. The data base consisted of two files, dissertation and journal. The information on the 107 theses including the master's theses and the doctoral dissertations from the Department of Scince Education, Seoul National University and on the 640 papers on science education from the first issues to the 1991 issues of five selected science education journals was input into the data base. The selected five Journals were Journal of the Korean Association for Research in Science Education(published by the Korean Association for Research in Science Education, 148 papers), Teaching Physics(published by Korean Physical Society, 164 papers),Chemical Education(published by The Korean Chemical Society, 98 papers), The Korean Journal of Biological Education(published by The Korean Society of Biological Education, 148 papers), and Journal of Science Education(published by Science Education Center, College of Education, Seoul National University,82 papers).

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.10
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• pp.830-836
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• 2005

Application of microarray technologies which monitor simultaneously the expression pattern of thousands of individual genes in different biological systems results in a tremendous increase of the amount of available gene expression data and have provided new insights into gene expression during drug development, within disease processes, and across species. There is a great need of data mining methods allowing straightforward interpretation, visualization and analysis of the relevant information contained in gene expression profiles. Specially, classifying biological samples into known classes or phenotypes is an important practical application for microarray gene expression profiles. Gene expression profiles obtained from tissue samples of patients thus allowcancer classification. In this research, molecular classification of microarray gene expression data is applied for multi-class cancer using computational biology such gene selection, principal component analysis and fuzzy clustering. The proposed method was applied to microarray data from leukemia patients; specifically, it was used to interpret the gene expression pattern and analyze the leukemia subtype whose expression profiles correlated with four cases of acute leukemia gene expression. A basic understanding of the microarray data analysis is also introduced.

• Progress in Medical Physics
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• v.28 no.1
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• pp.11-15
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• 2017

Relative biological effectiveness (RBE) of particle beam needs to be evaluated at particle beam therapy centers before the clinical application of the particle beam. However, since RBE analysis is implemented manually, it is useful to have a tool that can easily and effectively handle the data of experiments to generate cell survival curve and to analyze RBE simultaneously. In this work, the development of a program for RBE analysis of particle beam therapy was presented. This RBE analysis program was developed to include two parts; fitting the cell survival curves to linear-quadratic model and calculating the RBE values at a certain endpoint using fitting results. This program was also developed to simultaneously compare and analyze the template results that stored experiment data with photon and particle beam irradiations. The results of the cell survival curve obtained by each irradiation can be analyzed by the user on a desired data after reading the template stored in the easy-to-use excel file. The analysis results include the cell survival curves with error range, which are appeared in the screen and the ${\alpha}$ and ${\beta}$ parameters of linear-quadratic model with 95% confidence intervals, RBE values, and $R^2$ values to evaluate goodness-of-fit of survival curves to model, which are stored in a text cvs file. This software can generate cell survival curve, fit to model, and calculate RBE all at once with raw experiment data, so it helps users to save time for data handling and to reduce the possibility of making error on analysis. As a coming plan, we will create a user-friendly graphical user interface to present the results more intuitively.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.1
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• pp.14-26
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• 2012

The only extraterrestrial life detection experiments ever conducted were the three which were components of the 1976 Viking Mission to Mars. Of these, only the Labeled Release experiment obtained a clearly positive response. In this experiment $^{14}C$ radiolabeled nutrient was added to the Mars soil samples. Active soils exhibited rapid, substantial gas release. The gas was probably $CO_2$ and, possibly, other radiocarbon-containing gases. We have applied complexity analysis to the Viking LR data. Measures of mathematical complexity permit deep analysis of data structure along continua including signal vs. noise, entropy vs.negentropy, periodicity vs. aperiodicity, order vs. disorder etc. We have employed seven complexity variables, all derived from LR data, to show that Viking LR active responses can be distinguished from controls via cluster analysis and other multivariate techniques. Furthermore, Martian LR active response data cluster with known biological time series while the control data cluster with purely physical measures. We conclude that the complexity pattern seen in active experiments strongly suggests biology while the different pattern in the control responses is more likely to be non-biological. Control responses that exhibit relatively low initial order rapidly devolve into near-random noise, while the active experiments exhibit higher initial order which decays only slowly. This suggests a robust biological response. These analyses support the interpretation that the Viking LR experiment did detect extant microbial life on Mars.

• Molecules and Cells
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• v.26 no.2
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• pp.121-130
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• 2008

Methamphetamine, a commonly used addictive drug, is a powerful addictive stimulant that dramatically affects the CNS. Repeated METH administration leads to a rewarding effect in a state of addiction that includes sensitization, dependence, and other phenomena. It is well known that susceptibility to the development of addiction is influenced by sources of reinforcement, variable neuroadaptive mechanisms, and neurochemical changes that together lead to altered homeostasis of the brain reward system. These behavioral abnormalities reflect neuroadaptive changes in signal transduction function and cellular gene expression produced by repeated drug exposure. To provide a better understanding of addiction and the mechanism of the rewarding effect, it is important to identify related genes. In the present study, we performed gene expression profiling using microarray analysis in a reward effect animal model. We also investigated gene expression in four important regions of the brain, the nucleus accumbens, striatum, hippocampus, and cingulated cortex, and analyzed the data by two clustering methods. Genes related to signaling pathways including G-protein-coupled receptor-related pathways predominated among the identified genes. The genes identified in our study may contribute to the development of a gene modeling network for methamphetamine addiction.

• Journal of Korean Biological Nursing Science
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• v.16 no.1
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• pp.17-25
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• 2014

Purpose: The purpose of this study was to review the curriculum on biological nursing: structure and function of the human body, clinical microbiology, pathophysiology, and function and effect of drugs. Methods: Data was collected by searching and reviewing internet websites of 102 nursing schools or universities which provide 4 years nursing education in the Republic of Korea. The 74 curriculum on biological nursing science were available and analyzed by title, credits, hours, types of major (core or selective), offering semester, and laboratory practice. Results: The titles of 4 courses were diverse and were offered as core major (core requisites) or selective major. Structure and function of human body was offered in priority with more credits. Laboratory practice was poorly established in most courses. Biological nursing science courses were mostly taught in the second semester of the first year and the first or second semester of second year nursing education courses. Conclusion: There is a need to standardize the curriculum on biological nursing science and to expand the use of titles proposed by academic society. Also further research is necessary to identify curriculum details and to reflect the needs of professors.

• Genomics & Informatics
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• v.11 no.3
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• pp.142-148
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• 2013

SINE-VNTR-Alu (SVA) elements are present in hominoid primates and are divided into 6 subfamilies (SVA-A to SVA-F) and active in the human population. Using a bioinformatic tool, 22 SVA element-associated genes are identified in the human genome. In an analysis of genomic structure, SVA elements are detected in the 5′ untranslated region (UTR) of HGSNAT (SVA-B), MRGPRX3 (SVA-D), HYAL1 (SVA-F), TCHH (SVA-F), and ATXN2L (SVA-F) genes, while some elements are observed in the 3′UTR of SPICE1 (SVA-B), TDRKH (SVA-C), GOSR1 (SVA-D), BBS5 (SVA-D), NEK5 (SVA-D), ABHD2 (SVA-F), C1QTNF7 (SVA-F), ORC6L (SVA-F), TMEM69 (SVA-F), and CCDC137 (SVA-F) genes. They could contribute to exon extension or supplying poly A signals. LEPR (SVA-C), ALOX5 (SVA-D), PDS5B (SVA-D), and ABCA10 (SVA-F) genes also showed alternative transcripts by SVA exonization events. Dominant expression of HYAL1_SVA appeared in lung tissues, while HYAL1_noSVA showed ubiquitous expression in various human tissues. Expression of both transcripts (TDRKH_SVA and TDRKH_noSVA) of the TDRKH gene appeared to be ubiquitous. Taken together, these data suggest that SVA elements cause transcript isoforms that contribute to modulation of gene regulation in various human tissues.

• Journal of Ecology and Environment
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• v.40 no.2
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• pp.107-119
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• 2016

Background: Previous studies on the biological integrity on habitat and landuse patterns demonstrated ecological stream health in the view of regional or macrohabitat scale, thus ignored the mesoscale habitat patterns of pool, riffle, and runs in the stream health analysis. The objective of this study was to analyze influences on the mesohabitat structures of pool, riffle, and run reaches on the fish guilds and biological integrity in Geum-River Watershed. Results: The mesohabitat structures of pool, riffle, and run reaches influenced the ecological stream health along with some close relations on the fish trophic and tolerance guilds. The mesoscale components altered chemical water quality such as nutrients (TN, TP) and BOD and these, then, determined the primary productions, based on the sestonic chlorophyll-a. The riffle-reach had good chemical conditions, but the pool-reach had nutrient enrichments. The riffle-reach had a predominance of insectivores, while the pool-reach has a predominance of omnivores. Also, the riffle-reach had high proportions of sensitive fish and insectivore fish, and the pool-reach had high proportions of tolerant species in the community composition. The intermediate fish species in tolerance and omnivorous fish species in the food linkage dominated the community in the watershed, and the sensitive and insectivorous fishes decreased rapidly with a degradation of the water quality. All the habitat patterns were largely determined by the land-use patterns in the watershed. Conclusions: Trophic guilds and tolerance guilds of fish were determined by land-use pattern and these determined the stream health, based on the Index of Biological Integrity. This study remarks the necessity to include additional variables to consider information provided by mesohabitats and land-use distributions within the selected stream stretch. Overall, our data suggest that land-use pattern and mesohabitat distribution are important factors to be considered for the trophic and tolerance fish compositions and chemical gradients as well as ecological stream health in the watershed.