• Genomics & Informatics
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• v.20 no.4
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• pp.49.1-49.7
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• 2022

Many packages for a meta-analysis of genome-wide association studies (GWAS) have been developed to discover genetic variants. Although variations across studies must be considered, there are not many currently-accessible packages that estimate between-study heterogeneity. Thus, we propose a python based application called Beta-Meta which can easily process a meta-analysis by automatically selecting between a fixed effects and a random effects model based on heterogeneity. Beta-Meta implements flexible input data manipulation to allow multiple meta-analyses of different genotype-phenotype associations in a single process. It provides a step-by-step meta-analysis of GWAS for each association in the following order: heterogeneity test, two different calculations of an effect size and a p-value based on heterogeneity, and the Benjamini-Hochberg p-value adjustment. These methods enable users to validate the results of individual studies with greater statistical power and better estimation precision. We elaborate on these and illustrate them with examples from several studies of infertility-related disorders.

• Genomics & Informatics
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• v.10 no.1
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• pp.33-39
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• 2012

High-throughput genomic technologies (HGTs), including next-generation DNA sequencing (NGS), microarray, and serial analysis of gene expression (SAGE), have become effective experimental tools for cancer genomics to identify cancer-associated somatic genomic alterations and genes. The main hurdle in cancer genomics is to identify the real causative mutations or genes out of many candidates from an HGT-based cancer genomic analysis. One useful approach is to refer to known cancer genes and associated information. The list of known cancer genes can be used to determine candidates of cancer driver mutations, while cancer gene-related information, including gene expression, protein-protein interaction, and pathways, can be useful for scoring novel candidates. Some cancer gene or mutation databases exist for this purpose, but few specialized tools exist for an automated analysis of a long gene list from an HGT-based cancer genomic analysis. This report presents a new web-accessible bioinformatic tool, called CaGe, a cancer genome annotation system for the assessment of candidates of cancer genes from HGT-based cancer genomics. The tool provides users with information on cancer-related genes, mutations, pathways, and associated annotations through annotation and browsing functions. With this tool, researchers can classify their candidate genes from cancer genome studies into either previously reported or novel categories of cancer genes and gain insight into underlying carcinogenic mechanisms through a pathway analysis. We show the usefulness of CaGe by assessing its performance in annotating somatic mutations from a published small cell lung cancer study.

• Molecules and Cells
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• v.26 no.6
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• pp.595-605
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• 2008

Genome wide transcription analysis in response to stresses is essential to provide the basis of effective engineering strategies to improve stress tolerance in crop plants. In order to perform transcriptome analysis in Brassica rapa, we constructed a B. rapa oligo microarray, KBGP-24K, using sequence information from approximately 24,000 unigenes and analyzed cold ($4^{\circ}C$), salt (250 mM NaCl), and drought (air-dry) treated B. rapa plants. Among the B. rapa unigenes represented on the microarray, 417 (1.7%), 202 (0.8%), and 738 (3.1%) were identified as responsive genes that were differently expressed 5-fold or more at least once during a 48-h treatment with cold, salt, and drought, respectively. These results were confirmed by RT-PCR analysis. In the abiotic stress responsive genes identified, we found 56 transcription factor genes and 60 commonly responsive genes. It suggests that various transcriptional regulatory mechanisms and common signaling pathway are working together under the abiotic stresses in B. rapa. In conclusion, our new developed 24K oligo microarray will be a useful tool for transcriptome profiling and this work will provide valuable insight in the response to abiotic stress in B. rapa.

• Journal of Animal Science and Technology
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• v.63 no.1
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• pp.198-198
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• 2021

• Proceedings of the Korean Magnetic Resonance Society Conference
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• 2002.08a
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• pp.87-87
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• 2002

• Proceedings of the Korean Magnetic Resonance Society Conference
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• 2002.08a
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• pp.86-86
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• 2002

• Journal of Genetic Medicine
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• v.12 no.2
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• pp.96-99
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• 2015

Purpose: To evaluate the performance of the Momguard noninvasive prenatal test by tracing the 'screen positive' results based on preliminary samples from Korean cohorts. Materials and Methods: This preliminary study is based on data collected by the LabGenomics Clinical Laboratory (Seongnam, Korea) with informed consent. Only pregnant women who underwent both the Momguard test and karyotyping were included in this study. Momguard test results were compared with those of the karyotyping analysis. Results: Among the 38 cases with 'screen positive' results by Momguard, 30 cases also had karyotyping results available. In three trisomy (T) 18 and three T13 cases, the Momguard results were concordant with the karyotyping results. For the T21 cases, except for one case belonging to the mid-risk zone, Momguard results from 23 out of 24 cases matched the karyotyping results. Conclusion: Momguard is a highly reliable screening tool for detecting T13, T18, and T21 cases in independent Korean cohort samples.

• Molecular & Cellular Toxicology
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• v.2 no.4
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• pp.273-278
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• 2006

95 squamous cell lung carcinoma samples (normal tissue: 40 samples, tumor: 55 samples) were analyzed with 8 K cDNA microarray. 1-way ANOVA test was employed to select differentially expressed genes in tumor with FDR<0.01. Among the selected 1,655 genes, final 212 genes were chosen according to the expression fold change and used for following analysis. The expression of up-regulated 64 genes was verified with Reverse Transcription PCR and 10 genes were identified as candidates for SCC markers. In our opinion, those candidates can be exploited as diagnostic or therapeutic purposes. Gene Ontology (GO) based analysis was performed using those 212 genes, and following categories were revealed as significant biological processes: Immune response (GO: 0006955), antigen processing (GO: 0030333), inflammatory response (GO: 0006954), Cell adhesion (GO: 0007155), and Epidermis differentiation (GO: 0008544). Gene set enrichment analysis (GSEA) also carried out on overall gene expression profile with 522 functional gene sets. Glycolysis, cell cycle, K-ras and amino acid biosynthesis related gene sets were most distinguished. These results are consistent with the known characteristics of SCC and may be interconnected to rapid cell proliferation. However, the unexpected results from ERK activation in squamous cell carcinoma gripped our attention, and further studies are under progress.

• Proceedings of the Korean Society of Plant Biotechnology Conference
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• 2005.04a
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• pp.200-200
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• 2005

• Proceedings of the Korean Society of Crop Science Conference
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• 2019.09a
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• pp.151-151
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• 2019