• Molecules and Cells
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• v.46 no.1
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• pp.65-67
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• 2023

SMILES (simplified molecular-input line-entry system) information of small molecules parsed by one-hot array is passed to a convolutional neural network called black box. Outputs data representing a gene signature is then matched to the genetic signature of a disease to predict the appropriate small molecule. Efficacy of the predicted small molecules is examined by in vivo animal models. GSEA, gene set enrichment analysis.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.397-408
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• 2009

The development of microarray technology makes possible to analyse many thousands of genes simultaneously. While it is important to test each gene whether it shows changes in expression associated with a phenotype, human diseases are thought to occur through the interactions of multiple genes within a same functional cafe-gory. Recent research interests aims to directly test the behavior of sets of functionally related genes, instead of focusing on single genes. Gene set enrichment analysis(GSEA), significance analysis of microarray to gene-set analysis(SAM-GS) and parametric analysis of gene set enrichment(PAGE) have been applied widely as a tool for gene-set analyses. We describe their problems and propose an alternative method using a parametric analysis by adopting normal score transformation of gene expression values. Performance of the newly derived method is compared with previous methods on three real microarray datasets.

• Journal of KIISE:Software and Applications
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• v.37 no.1
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• pp.1-8
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• 2010

Recently lots of attention has been paid to gene set analysis for identifying differentially expressed gene-sets between two sample groups. Unlike earlier approaches, the gene set analysis enables us to find significant gene-sets along with their functional characteristics. For this reason, various novel approaches have been suggested lately for gene set analysis. As one of such, PAGE is a parametric approach that employs average difference (AD) as an expression metric to quantify expression differences between two sample groups and assumes that the distribution of gene scores is normal. This approach is preferred to non-parametric approach because of more effective performance. However, the metric AD does not reflect either gene expression intensities or variances over samples in calculating gene scores. Thus, in this paper, we investigate the usefulness of several other expression metrics for parametric gene-set analysis, which consider actual expression intensities of genes or their expression variances over samples. For this purpose, we examined three expression metrics, WAD (weighted average difference), FC (Fisher's criterion), and Abs_SNR (Absolute value of signal-to-noise ratio) for parametric gene set analysis and evaluated their experimental results.

• Journal of Life Science
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• v.29 no.1
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• pp.105-111
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• 2019

In recent years, progress has been made in the search for the development of new anti-cancer agents by employing specific inhibitors of histone deacetylase (HDAC)-6 to block signal transduction pathways in cancer cells. This study examined the effects of tubastatin A (TubA), an HDAC-6 inhibitor, on the growth and development of immature oocytes in murine ovaries using RNA sequencing analysis. The results from a gene set enrichment analysis (GSEA) indicated that the expression of most of the gene sets involved in the cell cycle and control and progression of meiosis decreased in the TubA-treated group as compared with that in germinal vesicle (GV) stage oocytes. In addition, an ingenuity pathway analysis (IPA) suggested that TubA not only caused increased expression of p53 and pRB and decreased expression of CDK4/6 and cyclin D but also caused elevated expression of genes involved in the control of the DNA check point in G2/M stage oocytes. These results suggest that TubA may induce cell cycle arrest and apoptosis through the induction of changes in the expression of genes involved in signal transduction pathways associated with DNA damage and the cell cycle of immature oocytes in the ovary.

• The Korean Journal of Applied Statistics
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• v.29 no.3
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• pp.437-448
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• 2016

Gene set analysis utilizing biologic information is expected to produce more interpretable results because the occurrence of tumors (or diseases) is believed to be associated with the regulation of related genes. Many methods have been developed to identify statistically significant gene sets across different phenotypes; however, most focus exclusively on either the differential gene expression or the differential correlation structure in the gene set. This research provides a new method that simultaneously considers the differential expression of genes and differential coexpression with multiple genes in the gene set. Application of this NEW method is illustrated with real microarray data example, p53; subsequently, a simulation study compares its type I error rate and power with GSEA, SAMGS, GSCA and GSNCA.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.8
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• pp.3899-3903
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• 2012

B7-H3 is a newly discovered member of the B7/CD28 superfamily which functions as an important T-cell immune molecule. It has been reported recently that B7-H3 is highly expressed in many cancer cells, the data indicating that it may be a regulation factor contributing to tumor-resistance. In our study, we used bioinformatics to identify differentially expressed genes between colonic cancer cells and normal colonic cells, aiming to analyze mechanisms and identify sub-pathways closely related to progression, with the final aim of finding small molecule drugs which might interfere this progression. We found that ajmaline is one related factor which may enhance self-immunity in colon carcinoma therapy and B7-H3 plays important roles with regard to immunoreactions of colonic cancer cells. All the results indicate that H7-B3 is a favorable prognostic biomarker for colon carcinomas, providing novel information regarding likely targets for intervention.

• Journal of the Korean Data and Information Science Society
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• v.23 no.1
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• pp.1-11
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• 2012

When the microarray experiment developed, main interest was limited to detect differentially expressed genes associated with a phenotype of interest. However, as human diseases are thought to occur through the interactions of multiple genes within a same functional category, the unit of analysis of the microarray experiment expanded to the set of genes. For the phenotype of censored survival time, Gene Set Enrichment Analysis(GSEA), Global test and Wald type test are widely used. In this paper, we modified the Wald type test by adopting normal score transformation of gene expression values and developed a parametric test which requires much less computation than others. The proposed method is compared with other methods using a real data set of ovarian cancer and a simulation data set.

• Journal of Ginseng Research
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• v.44 no.3
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• pp.519-526
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• 2020

Background: Bisphenol A (BPA), known as an endocrine disruptor, is widely used in the world. BPA is reported to cause inflammation-related diseases. Korean Red Ginseng (KRG) has been used safely in human for a long time for the treatment of diverse diseases. KRG has been reported of its mitigating effect on menopausal symptoms and suppress adipose inflammation. Here, we investigate the protective effect of orally administered KRG on the impacts of BPA in the liver and uterus of menopausal mice model. Methods: The transcriptome analysis for the effects of BPA on mice liver was evaluated by Gene Expression Omnibus (GEO) database-based data (GSE26728). In vivo assay to evaluate the protective effect of KRG on BPA impact in ovariectomized (OVX) mice were designed and analyzed by RNA sequencing. Results: We first demonstrated that BPA induced 12 kinds of gene set in the liver of normal mice. The administration of BPA and KRG did not change body, liver, and uterine weight in OVX mice. KRG downregulated BPA-induced inflammatory response and chemotaxis-related gene expression. Several gene set enrichment analysis (GSEA)-derived inflammatory response genes increased by BPA were inhibited by KRG in OVX mice. Conclusion: Our data suggest that BPA has commonly influenced inflammatory response effects on both normal and OVX mice. KRG protects against BPA impact of inflammatory response and chemotaxis in OVX mouse models. Our comparative analysis will provide new insight into the efficacy of KRG on endocrine disrupting chemicals and OVX mouse.

• 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.

• Journal of Ginseng Research
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• v.47 no.3
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• pp.469-478
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• 2023

Background: Nitrogen (N) is an essential macronutrient for plant growth and development. To support agricultural production and enhance crop yield, two major N sources, nitrate and ammonium, are applied as fertilizers to the soil. Although many studies have been conducted on N uptake and signal transduction, the molecular genetic mechanisms of N-mediated physiological roles, such as the secondary growth of storage roots, remain largely unknown. Methods: One-year-old P. ginseng seedlings treated with KNO₃ were analyzed for the secondary growth of storage roots. The histological paraffin sections were subjected to bright and polarized light microscopic analysis. Genome-wide RNA-seq and network analysis were carried out to dissect the molecular mechanism of nitrate-mediated promotion of ginseng storage root thickening. Results: Here, we report the positive effects of nitrate on storage root secondary growth in Panax ginseng. Exogenous nitrate supply to ginseng seedlings significantly increased the root secondary growth. Histological analysis indicated that the enhancement of root secondary growth could be attributed to the increase in cambium stem cell activity and the subsequent differentiation of cambium-derived storage parenchymal cells. RNA-seq and gene set enrichment analysis (GSEA) revealed that the formation of a transcriptional network comprising auxin, brassinosteroid (BR)-, ethylene-, and jasmonic acid (JA)-related genes mainly contributed to the secondary growth of ginseng storage roots. In addition, increased proliferation of cambium stem cells by a N-rich source inhibited the accumulation of starch granules in storage parenchymal cells. Conclusion: Thus, through the integration of bioinformatic and histological tissue analyses, we demonstrate that nitrate assimilation and signaling pathways are integrated into key biological processes that promote the secondary growth of P. ginseng storage roots.