• Genomics & Informatics
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• v.2 no.4
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• pp.180-183
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• 2004

Comparative Statistic Module(CSM) provides more reliable list of significant genes to genomics researchers by offering the commonly selected genes and a method of choice by calculating the rank of each statistical test based on the average ranking of common genes across the five statistical methods, i.e. t-test, Kruskal-Wallis (Wilcoxon signed rank) test, SAM, two sample multiple test, and Empirical Bayesian test. This statistical analysis module is implemented in Perl, and R languages.

• Molecular & Cellular Toxicology
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• v.1 no.4
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• pp.281-283
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• 2005

Extraction of biologically meaningful data and their validation are very important for toxicogenomics study because it deals with huge amount of heterogeneous data. BINGO is an annotation mining tool for biological interpretation of gene groups. Several statistical modeling approaches using Gene Ontology (GO) have been employed in many programs for that purpose. The statistical methodologies are useful in investigating the most significant GO attributes in a gene group, but the coherence of the resultant GO attributes over the entire group is rarely assessed. BINGO complements the statistical methods with graph-theoretic measures using the GO directed acyclic graph (DAG) structure. In addition, BINGO visualizes the consistency of a gene group more intuitively with a group-based GO subgraph. The input group can be any interesting list of genes or gene products regardless of its generation process if the group is built under a functional congruency hypothesis such as gene clusters from DNA microarray analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1243-1248
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• 2008

As development in technology of bioinformatics recently mates 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. In this thesis, we used CDNA microarrays of 3840 genes obtained from neuronal differentiation experiment of cortical stem cells on white mouse with cancer. It analyzed and compared performance of each of the experiment result using existing DT, NB, SVM and multi-perceptron neural network classifier combined the similar scale combination method after constructing class classification model by extracting significant gene list with a similar scale combination method proposed in this paper through normalization. Result classifying in Multi-Perceptron neural network classifier for selected 200 genes using combination of PC(Pearson correlation coefficient) and ED(Euclidean distance coefficient) represented the accuracy of 98.84%, which show that it improve classification performance than case to experiment using other classifier.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.2
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• pp.315-320
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• 2008

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 genome project. In such a thread, construction of gene expression analysis system and a basis rank analysis system is being watched newly. Recently, being identified fact that particular sub-class of tumor be related with particular chromosome, microarray started to be used in diagnosis field by doing cancer classification and predication based on gene expression information. In this thesis, we used cDNA microarrays of 3840 genes obtained from neuronal differentiation experiment of cortical stem cells on white mouse with cancer, created system that can extract informative gene list through normalization separately and proposed combination method for selecting more significant genes. And possibility of proposed system and method is verified through experiment. That result is that PC-ED combination represent 98.74% accurate and 0.04% MSE, which show that it improve classification performance than case to experiment after generating gene list using single similarity scale.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.5
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• pp.17-24
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• 2010

Recently the study of identifying bio-markers for disease diagnosis and prognosis has been actively performed. In particular, lots of attentions have been paid to the finding of pathway gene-sets differentially expressed in disease patients rather than the finding of individual gene markers. In this paper we propose a novel method to identify disease-related pathway gene-sets based on time-series microarray data. For this purpose, we firstly compute individual gene scores by the using maSigPro (microarray Significant Profiles) and then arrange all the genes in the decreasing order of the corresponding gene scores. The rank of each gene in the entire list is used to evaluate the statistical significance of candidate gene-sets with Wilcoxson rank sum test. For the generation of candidate gene-sets, MSigDB (Molecular Signatures Database) pathway information has been employed. The experiment was conducted with prostate cancer time-series microarray data and the results showed the usefulness of the proposed method by correctly identifying 6 out of 7 biological pathways already known as being actually related to prostate cancer.

• Korean Journal of Agricultural Science
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• v.48 no.2
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• pp.353-365
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• 2021

Previously, we reported that tissue factor (Tf) was included in the list of differentially expressed genes as an upregulated gene in a rejected porcine heart after xenotransplantation into monkey. In this study, we analyzed that expression of Tf in aortic endothelial cells (pAEC) isolated from alpha 1,3-galactosyltransferase knockout pig in response to allogeneic porcine serum and xenogeneic human serum. The consequence was significant upregulation of Tf expression by responding to human serum compared with porcine serum. To analyze the function of Tf gene as a promoter, we constructed reporter vectors for expression of luciferase linked to 1,246 and 787 base pairs of porcine Tf (pTF1246 and pTF787), and 535 base pairs of human TF (hTF535) sequences including putative promoter regions and AP-1 biding site at the 5' end. The reporter vectors were transfected into pAEC including cytomegalovirus enhancer/chicken β-actin (CAG)-luciferase vector as a control. Luciferase assay showed that all of the promoters were insufficient to express luciferase compared with CAG promoter in basic culture conditions. Notably, pTF1246, pTF787, and hTF535 led to a significant increase of luciferase expression in response to human serum compared with porcine serum while no change of CAG. pTF1246 and pTF787 showed higher expression than hTF535. Taken together, our findings suggest that pTF1246 and pTF787 promoters could mediate target gene expression specifically at xenogeneic stress condition.

• Herbal Formula Science
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• v.31 no.4
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• pp.295-313
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• 2023

Objectives : While treatments for cancer are advancing, the development of effective treatments for cancer metastasis, the main cause of cancer patient death, remains insufficient. Recent studies on Dichroae Radix have revealed that its active ingredients have the potential to inhibit cancer metastasis. This study aimed to investigate the cancer metastasis inhibitory effect of Dichroae Radix using network pharmacological analysis. Methods : The active compounds of Dichroae Radix have been identified using Traditional Chinese Medicine System Pharmacology Database and Analysis Platform. The UniProt database was used to collect each of information of all target proteins associated with the active compounds. To find the bio-metabolic processes associated with each target, the DAVID6.8 Gene Functional classifier tool was used. Compound-Target and Target-Pathway networks were analyzed via Cytoscape 3.40. Results : In total, 25 active compounds and their 62 non-redundant targets were selected through the TCMSP database and analysis platform. The target genes underwent gene ontology and pathway enrichment analysis. The gene list applied to the gene ontology analysis revealed associations with various biological processes, including signal transduction, chemical synaptic transmission, G-protein-coupled receptor signaling pathways, response to xenobiotic stimulus, and response to drugs, among others. A total of eleven genes, including HSP90AB1, CALM1, F2, AR, PAKACA, PTGS2, NOS2, RXRA, ESR1, ESR2, and NCOA1, were found to be associated with biological pathways related to cancer metastasis. Furthermore, nineteen of the active compounds from Dichroae Radix were confirmed to interact with these genes. Conclusions : The results provide valuable insights into the mechanism of action and molecular targets of Dichroae Radix. Notably, Berberine, the main active ingredient of Dichroae Radix, plays a significant role in degrading AR proteins in advanced prostate cancer. Further studies and validations can provide crucial data to advance cancer metastasis prevention and treatment strategies.

• Journal of Microbiology and Biotechnology
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• v.17 no.1
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• pp.154-161
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• 2007

Human immunodeficiency virus type 1 (HIV-1) infections are responsible for a substantial number of deaths annually and represent a significant threat to public health. According to the latest study, the Tat (Transactivator of transcription) protein is essential in transcription and replication of viral genes, and is among the early expression genes involved in the life cycle of HIV. The virion NC (nucleocapsid) plays an important role in early mRNA expression and contributes to the rapid viral replication that occurs during HIV-1 infection. Therefore, we attempted to elucidate the relationship between the Tat protein and nucleocapsid protein. In a comparison of two independently prepared and hybridized samples, flag NC overexpressed HEK 293T cells and pTat overexpressed HEK 293T cells, and hybridization showed the differences in expression in each case. Among the microarray results confirmed with real-time reverse transcriptase assay, twelve genes were identified to be involved according to their gene expression profiles. Of approximately 8,208 human genes that were analyzed, we monitored candidate genes that might have been related to NC and Tat genes from gene expression profiles. Additionally, the pathways could be viewed and analyzed through the use of Pathway Studio software. The pathways from the gene list were built and paths were found among the molecules/cell objects/processes by the curation method.

• Journal of Animal Science and Technology
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• v.65 no.1
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• pp.57-68
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• 2023

Flavor is an important sensory trait of chicken meat. The free amino acid (FAA) and nucleotide (NT) components of meat are major factors affecting meat flavor during the cooking process. As a genetic approach to improve meat flavor, we performed a genome-wide association study (GWAS) to identify the potential candidate genes related to the FAA and NT components of chicken breast meat. Measurements of FAA and NT components were recorded at the age of 10 weeks from 764 and 767 birds, respectively, using a White leghorn and Yeonsan ogye crossbred F2 chicken population. For genotyping, we used 60K Illumina single-nucleotide polymorphism (SNP) chips. We found a total of nine significant SNPs for five FAA traits (arginine, glycine, lysine, threonine content, and the essential FAAs and one NT trait (inosine content), and six significant genomic regions were identified, including three regions shared among the essential FAAs, arginine, and inosine content traits. A list of potential candidate genes in significant genomic regions was detected, including the KCNRG, KCNIP4, HOXA3, THSD7B, and MMUT genes. The essential FAAs had significant gene regions the same as arginine. The genes related to arginine content were involved in nitric oxide metabolism, while the inosine content was possibly affected by insulin activity. Moreover, the threonine content could be related to methylmalonyl-CoA mutase. The genes and SNPs identified in this study might be useful markers in chicken selection and breeding for chicken meat flavor.

• Molecules and Cells
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• v.39 no.4
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• pp.330-336
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• 2016

Long non-coding RNAs (lncRNAs) are involved in multiple cellular events, as well as in tumorigenesis. Colon cance-rassociated transcript-1 (CCAT1) gene encodes an lncRNA whose over-activation was observed in an expanding list of primary human solid tumors and tumor cell lines, however its biological roles in acute myeloid leukaemia (AML) has not been reported yet at present. In this study, the aberrant upregulation of CCAT1 was detected in French-American-British M4 and M5 subtypes of adult AML patients. By gain- and loss-of-function analysis, we determined that CCAT1 repressed monocytic differentiation and promoted cell growth of HL-60 by sequestering tumor suppressive miR-155. Accordingly, a significant decrease in miR-155 level was detected in AML patients. Reintroduction of miR-155 into HL-60 cells restored monocytic maturation and repressed cell proliferation. Furthermore, CCAT1 could up-regulated c-Myc via its competing endogenous RNA (ceRNA) activity on miR-155. In conclusion, these results revealed new mechanism of lncRNA CCAT1 in AML development, and suggested that the manipulation of CCAT1 expression could serve as a potential strategy in AML therapy.