• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.197-207
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• 2010

Using a variety of data-mining methods on high-throughput cDNA microarray data, the level of gene expression in two different tissues can be compared, and DEG(Differentially Expressed Gene) genes in between normal cell and tumor cell can be detected. Diagnosis can be made with these genes, and also treatment strategy can be determined according to the cancer stages. Existing cancer classification methods using machine learning select the marker genes which are differential expressed in normal and tumor samples, and build a classifier using those marker genes. However, in addition to the differences in gene expression levels, the difference in gene-gene correlations between two conditions could be a good marker in disease diagnosis. In this study, we identify gene pairs with a big correlation difference in two sets of samples, build gene classification modules using these gene pairs. This cancer classification method using gene modules achieves higher accuracy than current methods. The implementing clinical kit can be considered since the number of genes in classification module is small. For future study, Authors plan to identify novel cancer-related genes with functionality analysis on the genes in a classification module through GO(Gene Ontology) enrichment validation, and to extend the classification module into gene regulatory networks.

• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.4
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• pp.242-249
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• 2021

Forage crop management is severely challenged by global warming-induced climate changes representing diverse a/biotic stresses. Thus, screening of valuable genetic resources would be applied to develop stress-tolerant forage crops. We isolated two NAC (NAM, ATAF1, ATAF2, CUC2) transcription factors (ANAC032 and ANAC083) transcriptionally activated by multi-abiotic stresses (salt, drought, and cold stresses) from Arabidopsis by microarray analysis. The NAC family is one of the most prominent transcription factor families in plants and functions in various biological processes. The enhanced expressions of two ANACs by multi-abiotic stresses were validated by quantitative RT-PCR analysis. We also confirmed that both ANACs were localized in the nucleus, suggesting that ANAC032 and ANAC083 act as transcription factors to regulate the expression of downstream target genes. Promoter activities of ANAC032 and ANAC083 through histochemical GUS staining again suggested that various abiotic stresses strongly drive both ANACs expressions. Our data suggest that ANAC032 and ANAC083 would be valuable genetic candidates for breeding multi-abiotic stress-tolerant forage crops via the genetic modification of a single gene.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.1629-1633
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• 2013

Background: Gene set analysis (GSA) incorporates biological with statistical knowledge to identify gene sets which are differentially expressed that between two or more phenotypes. Materials and Methods: In this paper gene sets differentially expressed between acute lymphoblastic leukaemia (ALL) with BCR-ABL and those with no observed cytogenetic abnormalities were determined by GSA methods. The BCR-ABL is an abnormal gene found in some people with ALL. Results: The results of two GSAs showed that the Category test identified 30 gene sets differentially expressed between two phenotypes, while the Hotelling's $T^2$ could discover just 19 gene sets. On the other hand, assessment of common genes among significant gene sets showed that there were high agreement between the results of GSA and the findings of biologists. In addition, the performance of these methods was compared by simulated and ALL data. Conclusions: The results on simulated data indicated decrease in the type I error rate and increase the power in multivariate (Hotelling's $T^2$) test as increasing the correlation between gene pairs in contrast to the univariate (Category) test.

• Molecules and Cells
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• v.24 no.2
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• pp.200-209
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• 2007

We generated gene expression data from the tissues of 50 gastric cancer patients, and applied meta-analysis and gene set analysis to this data and three other stomach cancer gene expression data sets to define the gene expression changes in gastric tumors. By meta-analysis we identified genes consistently changed in gastric carcinomas, while gene set analysis revealed consistently changed biological themes. Genes and gene sets involved in digestion, fatty acid metabolism, and ion transport were consistently down-regulated in gastric carcinomas, while those involved in cellular proliferation, cell cycle, and DNA replication were consistently up-regulated. We also found significant differences between the genes and gene sets expressed in diffuse and intestinal type gastric carcinoma. By gene set analysis of cytogenetic bands, we identified many chromosomal regions with possible gross chromosomal changes (amplifications or deletions). Similar analysis of transcription factor binding sites (TFBSs), revealed transcription factors that may have caused the observed gene expression changes in gastric carcinomas, and we confirmed the overexpression of one of these, E2F1, in many gastric carcinomas by tissue array and immunohistochemistry. We have incorporated the results of our meta- and gene set analyses into a web accessible database (http://human-genome.kribb.re.kr/stomach/).

• Journal of Korean Neurosurgical Society
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• v.65 no.5
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• pp.697-709
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• 2022

Objective : The present study aimed to identify the function of ischemic stroke (IS) patients' peripheral blood and its role in IS, explore the pathogenesis, and provide direction for clinical research progress by comprehensive bioinformatics analysis. Methods : Two datasets, including GSE58294 and GSE22255, were downloaded from Gene Expression Omnibus database. GEO2R was utilized to obtain differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed using the database annotation, visualization and integrated discovery database. The protein-protein interaction (PPI) network of DEGs was constructed by search tool of searching interactive gene and visualized by Cytoscape software, and then the Hub gene was identified by degree analysis. The microRNA (miRNA) and miRNA target genes closely related to the onset of stroke were obtained through the miRNA gene regulatory network. Results : In total, 36 DEGs, containing 27 up-regulated and nine down-regulated DEGs, were identified. GO functional analysis showed that these DEGs were involved in regulation of apoptotic process, cytoplasm, protein binding and other biological processes. KEGG enrichment analysis showed that these DEGs mediated signaling pathways, including human T-cell lymphotropic virus (HTLV)-I infection and microRNAs in cancer. The results of PPI network and cytohubba showed that there was a relationship between DEGs, and five hub genes related to stroke were obtained : SOCS3, KRAS, PTGS2, EGR1, and DUSP1. Combined with the visualization of DEG-miRNAs, hsa-mir-16-5p, hsa-mir-181a-5p and hsa-mir-124-3p were predicted to be the key miRNAs in stroke, and three miRNAs were related to hub gene. Conclusion : Thirty-six DEGs, five Hub genes, and three miRNA were obtained from bioinformatics analysis of IS microarray data, which might provide potential targets for diagnosis and treatment of IS.

• Genomics & Informatics
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• v.5 no.1
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• pp.10-18
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• 2007

Numerous studies have reported that genes with similar expression patterns are co-regulated. From gene expression data, we have assumed that genes having similar expression pattern would share similar transcription factor binding sites (TFBSs). These function as the binding regions for transcription factors (TFs) and thereby regulate gene expression. In this context, various analysis tools have been developed. However, they have shortcomings in the combined analysis of expression patterns and significant TFBSs and in the functional analysis of target genes of significantly overrepresented putative regulators. In this study, we present a web-based A Functional Clustering Analysis Tool for Predicted Transcription Regulatory Elements and Gene Ontology Terms (FCAnalyzer). This system integrates microarray clustering data with similar expression patterns, and TFBS data in each cluster. FCAnalyzer is designed to perform two independent clustering procedures. The first process clusters gene expression profiles using the K-means clustering method, and the second process clusters predicted TFBSs in the upstream region of previously clustered genes using the hierarchical biclustering method for simultaneous grouping of genes and samples. This system offers retrieved information for predicted TFBSs in each cluster using $Match^{TM}$ in the TRANSFAC database. We used gene ontology term analysis for functional annotation of genes in the same cluster. We also provide the user with a combinatorial TFBS analysis of TFBS pairs. The enrichment of TFBS analysis and GO term analysis is statistically by the calculation of P values based on Fisher’s exact test, hypergeometric distribution and Bonferroni correction. FCAnalyzer is a web-based, user-friendly functional clustering analysis system that facilitates the transcriptional regulatory analysis of co-expressed genes. This system presents the analyses of clustered genes, significant TFBSs, significantly enriched TFBS combinations, their target genes and TFBS-TF pairs.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6347-6350
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• 2013

Post-transplant lymphoproliferative disorder (PTLD) is a common complication of therapeutic immunosuppression after organ transplantation. Gene expression profile facilitates the identification of biological difference between Epstein-Barr virus (EBV) positive and negative PTLDs. Previous studies mainly implemented variance/regression analysis without considering unaccounted array specific factors. The aim of this study is to investigate the gene expression difference between EBV positive and negative PTLDs through partial least squares (PLS) based analysis. With a microarray data set from the Gene Expression Omnibus database, we performed PLS based analysis. We acquired 1188 differentially expressed genes. Pathway and Gene Ontology enrichment analysis identified significantly over-representation of dysregulated genes in immune response and cancer related biological processes. Network analysis identified three hub genes with degrees higher than 15, including CREBBP, ATXN1, and PML. Proteins encoded by CREBBP and PML have been reported to be interact with EBV before. Our findings shed light on expression distinction of EBV positive and negative PTLDs with the hope to offer theoretical support for future therapeutic study.

• Korean Journal of Acupuncture
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• v.23 no.3
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• pp.133-160
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• 2006

Objectives : Scolopendrae Corpus has a broad array of clinical applications in Korean medicine, including treatment of inflammatory conditions such as arthritis. To explore the global gene expression profiles in human Raw cell lines treated with Scolopendrae Corpus herbal-acupuncture solution (SCHAS), cDNA microarray analysis was performed. Methods : The Raw 264.7 cells were treated with lipopolysaccharide (LPS), SCHAS, or both. The primary data was normalized by the total spots of intensity between two groups, and then normalized by the intensity ratio of reference genes such as housekeeping genes in both groups. The expression ratio was converted to log2 ratio. Normalized spot intensities were calculated into gene expression ratios between the control and treatment groups. Greater than 2 fold changes between two groups were considered to be of significance. Results : Of the 8 K genes profiled in this study, with a cut-off level of two-fold change in the expression, 20 genes (BCL2-related protein A1, MARCKS-like 1, etc.) were upregulated and 5 genes (activated RNA polymerase II transcription cofactor 4, calcium binding atopy-related autoantigen 1, etc.) downregulated following LPS treatment. 139 genes (kell blood group precursor (McLeod phenotype), ribosomal protein S7, etc.) were upregulated and 42 genes (anterior gradient 2 homolog (xenopus laevis), phosphodiesterase 8B, etc.) were downregulated following SCHAS treatment. And 10 genes (yeast saccharomyces cerevisiae intergeneic sequence 4-1, mitogen-activated protein kinase 1, etc.) were upregulated and 8 genes (spermatid perinuclear RNA binding protein, nuclear receptor binding protein 2, etc.) were downregulated following co-stimulation of SCHAS and LPS. Discussions : It is thought that microarrays will play an ever-growing role in the advance of our understanding of the pharmacological actions of SCHAS in the treatment of arthritis. But further studies are required to concretely prove the effectiveness of SCHAS.

• Korean Journal of Oriental Medicine
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• v.8 no.2 s.9
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• pp.95-107
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• 2002

Yukmijihwang-tang(YM) is a noted herbal prescription in Chinese and Korean traditional medicines, and it has been known to reinforce the vital essence and has been widely used for a variety of disease such as stroke, osteoporosis, anti-tumor, and hypothyrodism. Regarding its traditional use, YM has been known to reinforce the Yin (vital essence) of liver and kidney. Also it has been known to reinforce nutrition and biological function in brain. Recently, studies suggested that YM increase antioxidant activities and exert the protective effect against oxidant-induced liver cell injury. We investigated the high-throughput gene expression analysis on the Yukmijihwang-tang administrated in SD rats. Microarray data were validated on a limited number of genes by semiquantitative RT-PCR and Western blot analyses. The recent availability of microarrays provides an attractive strategy for elaborating an unbiased molecular profile of large number of genes in drug discovery This experimental approach offers the potential to identify molecules or cellular pathways not previously associated with herbal medicine. Total RNA from normal control brain and Yukmijihwang-tang administrated brain were hybridized to microarrays containing 10,000 rat genes. The 52 genes were found to be up-regulated(twice or more) excluding EST gene. The nine genes were found to be down-regulated(twice or more) excluding EST gene. Gene array technology was used to identify for the first time many genes expression pathway analysis that arecell cycle pathway, apoptosis pathway, electron transport chain pathway, cytoplasmic ribosomal protein pathway, fatty acid degradation pathway, and TGF-beta signaling pathway. These differentially expressed genes pathway analysis have not previously been iavestigated in the context of herbal medicine efficacy and represent novel factors for further study of the mechanism of herbal medicine efficacy.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.145-148
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• 2007

생명과학분야에서 마이크로어레이 기술은 세포에서의 RNA 발현 프로파일을 관찰할 수 있도록 함으로써 생명현상의 규명 및 약물개발 둥에서 분자수준의 생명현상에 대한 관찰과 분석이 가능 해지고 있다. 마이크로어레이 데이터분석에서는 특정한 처리나 과정에서 현저한 특성을 보이는 유전자를 식별하기 위한 분석뿐만 아니라 유전자 전체인 게놈수준에서의 분석도 이루어진다. 최근 유전자의 발현이 다양한 조절, 신호전달 및 대사경로에 의해서 영향을 받고 있다는 관점에서 게놈수준의 분석에 관심이 증가하고 있다. 약물반응 실험에서는 약물에 대한 게놈수준의 발현 프로파일을 관찰하는 것도 많은 정보를 제공할 수 있다. 약물실험에서는 대조군과 실험군들간에 관심 있는 상대적인 발현특성을 갖는 유전자군을 전체적으로 추출하는 것이 필요한 경우가 있다. 예를 들면 정상군은 두개의 실험군에 대해서 중간청도의 발현정도를 갖는 유전자군을 식별하는 분석을 하는 경우, 생물학적인 데이터의 특성상 절대값을 비교하는 방법으로는 유용한 유전자들을 효과적으로 식별해 낼 수 없다. 이 논문에서는 정상군과 실험군들의 발현정도값의 경향을 판단하기 위해서 각 유전자에 대해서 집단별 대표값을 선정하여 퍼지집합으로 집단의 값의 범위를 결정하고, 이를 이용하여 특정 패턴을 갖는 유전자들을 식별해내는 방법을 제안하고, 실제 데이터를 통해서 실험한 결과를 보인다.