• 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 Embryo Transfer
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• v.30 no.2
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• pp.99-107
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• 2015

The aim of the present study was to identify coat color associated genes that are differentially expressed in mature Korean brindle cattle (KBC) with different coat colors and in Hanwoo cows. KBC calves, before and after coat color appearance, were included. Total cellular RNA was isolated from the tail hair cells and used for microarray. The number of expressed coat color associated genes/probes was 5813 in mature KBC and Hanwoo cows. Among the expressed coat color associated genes/probes, 167 genes were the coat color associated genes listed in the Gene card database and 125 genes were the pigment and melanocyte genes listed in the Gene ontology_bovine database. There were 23 genes/probes commonly listed in both databases and their expressions were further studied. Out of the 23 genes/probes, MLPH, PMEL, TYR and TYRP1 genes were expressed at least two fold higher (p<0.01) levels in KBC with brindle color than either Hanwoo or KBC with brown color. TYRP1 expression was 22.96 or 19.89 fold higher (p<0.01) in KBC with brindle color than either Hanwoo or KBC with brown color, respectively, which was the biggest fold difference. The hierarchical clustering analysis indicated that MLPH, PMEL, TYR and TYRP1 were the highly expressed genes in mature cattle. There were only a few genes differentially expressed after coat color appearance in KBC calves. Studies on the regulation and mechanism of gene expression of highly expressed genes would be next steps to better understand coat color determination and to improve brindle coat color appearance in KBC.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1924-1929
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• 2007

Nowadays, a lot of related data obtained from these research could be given a new present meaning to accomplish the original purpose of the whole research as a human project. The method of tumor classification based on microarray could contribute to being accurate tumor classification by finding differently expressing gene pattern statistically according to a tumor type. Therefore, the process to select a closely related informative gene with a particular tumor classification to classify tumor using present microarray technology with effect is essential. In this thesis, we used cDNA microarrays of 3840 genes obtained from neuronal differentiation experiment of cortical stem cells on white mouse with cancer, constructed accurate tumor classification model by extracting informative gene list through normalization separately and then did performance estimation by analyzing and comparing each of the experiment results. Result classifying Multi-Perceptron classifier for selected genes using Pearson correlation coefficient represented the accuracy of 95.6%.

• The Journal of Internal Korean Medicine
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• v.30 no.3
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• pp.594-603
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• 2009

Objectives : ICH breaks down blood vessels within the brain parenchyma, which finally leads to neuronal loss, drugs to treat ICH have not yet been established. In this experiment, we measured the effect of Woowhangchongshim-won (WWCSW) on intracerebral hemorrhage (ICH) in rat using microarray technology. Methods : We measured the effect of WWCSW on ICH in rat using microarray technology. ICH was induced by injection of collagenase type IV, and total RNA was isolated. Image files of microarray were measured using a ScanArray scanner, and the criteria of the threshold for up- and down-regulation was 2 fold. Hierarchical clustering was implemented using CLUSTER and TREEVIEW program, and for Ontology analysis. GOSTAT program was applied in which p-value was calculated by Chi square or Fisher's exact test based on the total array element. Results : WWCSW-treatment restored the gene expression altered by ICH-induction in brain to the levels of 76.0% and 70.1% for up- and down-regulated genes, respectively. Conclusion : Co-regulated genes by ICH model of rat could be used as molecular targets for therapeutic effects of drug including WWCSW. That is, the presence of co-regulated genes may represent the importance of these genes in ICH in the brain and the change of expression level of these co-regulated genes would also indicate the functional change of brain tissue.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2283-2288
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• 2006

As development in technology of bioinformatics recently makes it possible to operate micro-level experiments, we can observe the expression pattern of total genome through on chip and analyze the interactions of thousands of genes at the same time. Thus, DNA microarray technology presents the new directions of understandings for complex organisms. Therefore, it is required how to analyze the enormous gene information obtained through this technology effectively. In this thesis, We used sample data of bioinformatics core group in harvard university. It designed and implemented system that evaluate accuracy after dividing in class of two using Bayesian algorithm, ASA, of feature extraction method through normalization process, reducing or removing of noise that occupy by various factor in microarray experiment. It was represented accuracy of 98.23% after Lowess normalization.

• Proceedings of the Korean Society of Life Science Conference
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• 2000.06a
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• pp.3-8
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• 2000

The complete genome sequence of a Gram-positive bacterium .Bacillus subtilis has recently been reported and it is now clear that more than 50% of its ORFs have no known function (1). To study the global gene expression in B. subtilis at single gene resolution, we have tested the glass DNA microarrays in a step-wise fashion. As a preliminary experiment, we have created arrays of PCR products for 14 ORF whose transcription patterns have been well established through transcriptional mapping analysis. We measured changes in mRNA transcript levels between early exponential and stationary phase by hybridizing fluorescently labeled cDNA (with Cy3-UTP and Cy5-UTP) onto the array. We then compared the microarray data to confirm that the transcription patterns of these genes are well consistent with the known Northern analysis data. Since the preliminary test has been successful, we scaled up the experiments to ${\sim}$94% of the 4,100 annotated ORFs for the complete genome sequence of B. subtilis. Using this whole genomic microarray, we searched genes that are catabolite-repressive and those that are under the control of ${\sigma}^{Y}$, one of the functionally unknown ECF sigma factors. From these results, we here report that we have established DNA microarray techniques that are applicable for the whole genome of B. subtilis.

• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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• pp.85-90
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• 2002

Microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. In time-course experiments in which gene expression is monitored over time we are interested in testing gene expression profiles for different experimental groups. We propose a statistical test based on the ANOVA model to identify genes that have different gene expression profiles among experimental groups in time-course experiments. Using this test, we can detect genes that have different gene expression profiles among experimental groups. The proposed model is illustrated using cDNA microarrays of 3,840 genes obtained in an experiment to search for changes in gene expression profiles during neuronal differentiation of cortical stem cells.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1103-1113
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• 2011

Gene expression data is obtained through many stages of an experiment and errors produced during the process may cause missing values. Due to the distinctness of the data so called 'small n large p', genes have to be selected for statistical analysis, like classification analysis. For this reason, imputation and gene selection are important in a microarray data analysis. In the literature, imputation, gene selection and classification analysis have been studied respectively. However, imputation, gene selection and classification analysis are sequential processing. For this aspect, we compare the performance of classification methods after imputation and gene selection methods are applied to microarray data. Numerical simulations are carried out to evaluate the classification methods that use various combinations of the imputation and gene selection methods.

• The Korean Journal of Applied Statistics
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• v.21 no.3
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• pp.523-535
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• 2008

Initial work of microarray data analysis focused on identification of differentially expressed genes, and recently, the focus has moved to discovering significant sets of functionally related genes. We describe some problems of GSEA and PAGE, and propose a modified method to identify significant gene sets. The results based on a simulated experiment and real data analysis using a set of publicly available data show the superiority of the newly proposed method, GSA-AT, in detecting significant pathways with the accurate prediction.

• Genomics & Informatics
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• v.4 no.3
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• pp.129-132
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• 2006

Toxicogenomics has recently emerged in the field of toxicology and the DNA microarray technique has become common strategy for predictive toxicology which studies molecular mechanism caused by exposure of chemical or environmental stress. Although microarray experiment offers extensive genomic information to the researchers, yet high dimensional characteristic of the data often makes it hard to extract meaningful result. Therefore we developed toxicant enrichment analysis similar to the common enrichment approach. We also developed web-based system graPT to enable considerable prediction of toxic endpoints of experimental chemical.