• Proceedings of the KSRS Conference
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• v.2
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• pp.623-626
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• 2006

Group of genes controls the functioning of a cell by complex interactions. These interacting gene groups are called Gene Regulatory Networks (GRNs). Two previous data mining approaches, clustering and classification have been used to analyze gene expression data. While these mining tools are useful for determining membership of genes by homology, they don't identify the regulatory relationships among genes found in the same class of molecular actions. Furthermore, we need to understand the mechanism of how genes relate and how they regulate one another. In order to detect regulatory relationships among genes from time-series Microarray data, we propose a novel approach using frequent pattern mining and chain rule. In this approach, we propose a method for transforming gene expression data to make suitable for frequent pattern mining, and detect gene expression patterns applying FP-growth algorithm. And then, we construct gene regulatory network from frequent gene patterns using chain rule. Finally, we validated our proposed method by showing that our experimental results are consistent with published results.

• Proceedings of the Microbiological Society of Korea Conference
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• 2002.10a
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• pp.27-30
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• 2002

Ralstonia eutrupha JMP134 is a well-known soil bacterium which can metabolite diverse aromatic compounds and xenobiotics, such as phenol, 2,4-dichlorophenoxy acetic acid (2, 4-D), and trichloroethylene (TCE), etc. Phenol is degraded through chromosomally encoded phenol degradation pathway. Phenol is first metabolized into catechol by a multicomponent phenol hydroxylase, which is further metabolized to TCA cycle intermediates via a meta-cleavage pathway. The nucleotide sequences of the genes for the phenol hydroxylase have previously been determined, and found to composed of eight genes phlKLMNOPRX in an operon structure. The phlR, whose gene product is a NtrC-like transcriptional activator, was found to be located at the internal region of the structural genes, which is not the case in most bacteria where the regulatory genes lie near the structural genes. In addition to this regulatory gene, we found other regulatory genes, the phlA and phlR2, downstream of the phlX. These genes were found to be overlapped and hence likely to be co-transcribed. The protein similarity analysis has revealed that the PhlA belongs to the GntR family, which are known to be negative regulators, whereas the PhlR2 shares high homology with the NtrC-type family of transcriptional activators like the PhlR. Disruption of the phlA by insertional mutation has led to the constitutive expression of the activity of phenol hydroxylase in JMP134, indicating that PhlA is a negative regulator. Possible regulatory mechanisms of phenol metabolism in R. eutropha JMP134 has been discussed.

• Genomics & Informatics
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• v.13 no.3
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• pp.76-80
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• 2015

Type 2 diabetes mellitus is a complex metabolic disorder associated with multiple genetic, developmental and environmental factors. The recent advances in gene expression microarray technologies as well as network-based analysis methodologies provide groundbreaking opportunities to study type 2 diabetes mellitus. In the present study, we used previously published gene expression microarray datasets of human skeletal muscle samples collected from 20 insulin sensitive individuals before and after insulin treatment in order to construct insulin-mediated regulatory network. Based on a motif discovery method implemented by iRegulon, a Cytoscape app, we identified 25 candidate regulons, motifs of which were enriched among the promoters of 478 up-regulated genes and 82 down-regulated genes. We then looked for a hierarchical network of the candidate regulators, in such a way that the conditional combination of their expression changes may explain those of their target genes. Using Genomica, a software tool for regulatory network construction, we obtained a hierarchical network of eight regulons that were used to map insulin downstream signaling network. Taken together, the results illustrate the benefits of combining completely different methods such as motif-based regulatory factor discovery and expression level-based construction of regulatory network of their target genes in understanding insulin induced biological processes and signaling pathways.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.105-113
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• 2007

A gene regulatory network is a network of genes representing how genes influence the activities of other genes. Nowadays from microarray experiments, a large number of measurements on the expression levels of genes are available. One of typical data is the so-called "steady-state model" data measuring the expression levels of other genes after knocking out a particular gene. This paper shows how to reverse engineer a parsimonious gene regulatory network, using these measurement data. Our model considers auto-regulation, which forms a cycle in a genetic network. We also model repressor and enhancer roles of genes. which are not considered in previous known methods.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.2
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• pp.457-463
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• 2015

The pathogenesis of mantle cell lymphoma, a special subtype of lymphoma that is invasive and indolent and has a median survival of 3 to 4 years, is still partially unexplained. Much research about genes and miRNAs has been conducted in recent years, but interactions and regulatory relations of genetic elements which may play a vital role in genesis of MCL have attracted only limited attention. The present study concentrated on regulatory relations about genes and miRNAs contributing to MCL pathogenesis. Numerous experimentally validated raw data were organized into three topology networks, comprising differentially expressed, associated and global examples. Comparison of similarities and dissimilarities of the three regulating networks, paired with the analysis of the interactions between pairs of elements in every network, revealed that the differentially expressed network illuminated the carcinogenicity mechanism of MCL and the related network further described the regulatory relations involved, including prevention, diagnosis, development and therapy. Three kinds of regulatory relations for host genes including miRNAs, miRNAs targeting genes and genes regulating miRNAs were concluded macroscopically. Regulation of the differentially expressed miRNAs was also analyzed, in terms of abnormal gene expression affecting the MCL pathogenesis. Special regulatory relations were uncovered. For example, auto-regulatory loops were found in the three topology networks, key pathways of the nodes being highlighted. The present study focused on a novel point of view revealing important influencing factors for MCL pathogenesis.

• The KIPS Transactions:PartD
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• v.14D no.1 s.111
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• pp.9-20
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• 2007

Groups of genes control the functioning of a cell by complex interactions. Such interactions of gene groups are tailed Gene Regulatory Networks(GRNs). Two previous data mining approaches, clustering and classification, have been used to analyze gene expression data. Though these mining tools are useful for determining membership of genes by homology, they don't identify the regulatory relationships among genes found in the same class of molecular actions. Furthermore, we need to understand the mechanism of how genes relate and how they regulate one another. In order to detect regulatory relationships among genes from time-series Microarray data, we propose a novel approach using frequent pattern mining and chain rules. In this approach, we propose a method for transforming gene expression data to make suitable for frequent pattern mining, and gene expression patterns we detected by applying the FP-growth algorithm. Next, we construct a gene regulatory network from frequent gene patterns using chain rules. Finally, we validate our proposed method through our experimental results, which are consistent with published results.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.2
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• pp.475-483
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• 2015

Genes and microRNAs (miRNAs) have important roles in human oncology. However, most of the biological factors are reported in disperse form which makes it hard to discover the pathology. In this study, genes and miRNAs involved in human endometrial cancer(EC) were collected and formed into regulatory networks following their interactive relations, including miRNAs targeting genes, transcription factors (TFs) regulating miRNAs and miRNAs included in their host genes. Networks are constructed hierarchically at three levels: differentially expressed, related and global. Among the three, the differentially expressed network is the most important and fundamental network that contains the key genes and miRNAs in EC. The target genes, TFs and miRNAs are differentially expressed in EC so that any mutation in them may impact on EC development. Some key pathways in networks were highlighted to analyze how they interactively influence other factors and carcinogenesis. Upstream and downstream pathways of the differentially expressed genes and miRNAs were compared and analyzed. The purpose of this study was to partially reveal the deep regulatory mechanisms in EC using a new method that combines comprehensive genes and miRNAs together with their relationships. It may contribute to cancer prevention and gene therapy of EC.

• Journal of Microbiology and Biotechnology
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• v.17 no.2
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• pp.244-252
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• 2007

Escherichia coli has a PhoR-PhoB two-component regulatory system to detect and respond to the changes of environmental phosphate concentration. For the E. coli W3110 strain growing under phosphate-limiting condition, the changes of global gene expression levels were investigated by using DNA microarray analysis. The expression levels of some genes that are involved in phosphate metabolism were increased as phosphate became limited, whereas those of the genes involved in ribosomal protein or amino acid metabolism were decreased, owing to the stationary phase response. The upregulated genes could be divided into temporarily and permanently inducible genes by phosphate starvation. At the peak point showing the highest expression levels of the phoB and phoR genes under phosphate-limiting condition, the phoB- and/or phoR-dependent regulatory mechanisms were investigated in detail by comparing the gene expression levels among the wild-type and phoB and/or phoR mutant strains. Overall, the phoB mutation was epistatic over the phoR mutation. It was found that PhoBR and PhoB were responsible for the upregulation of the phosphonate or glycerol phosphate metabolism and high-affinity phosphate transport system, respectively. These results show the complex regulation by the PhoR-PhoB two-component regulatory system in E. coli.

• Journal of Microbiology
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• v.40 no.1
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• pp.43-50
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• 2002

A cluster of genes encoding the pyruvate dehydrogenase complex (PDC) of Streptomyces seoulensis, a Gram-positive bacterium, was cloned and sequenced. The genes of S. seoulensis consist of four open reading frames. The first gene, lpd, which encodes a lipoamide dehydrogenase, is followed by pdhB encoding a dihydrolipoamide acetyltransferase (E2p), pdhR, a regulatory gene, and pdhA encoding a pyruvate dehydrogenase component (Elp). Elp had an unusual homodimeric subunit, which has been known only in Gram-negative bacteria S. seoulensis E2p contains two lipoyl domains like those of humans and Streptomyces faecalis. The pdhR gene appears to be clustered with the structural genes of S. seoulensis PDC. The PdhR-overexpressed S. seoulensis howed growth retardation and the decrease of Elp, indicating that PdhR regulates the function of PDC by repressing the expression of Elp. A strain of Streptomyces licidans overexpressing S. seoulensis PdhR showed a significant decreasein the level of actinorhodin, implying a regulatory role for Streptomyces PDC in antibiotic biosynthesis.

• Journal of Life Science
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• v.5 no.4
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• pp.162-169
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• 1995

The glpD genes encoding gly-3-p dehydrogenase is essential for the aerobic growth of E. coli on glycerol or gly-3-p. The glpE gene, the function of which is unknownm is transcribed divergently with respect to glpD gene. Expression of the adjacent but divergently transcribed glpD the glpE genes is positively regulated by the cAMP-CRP complex. In this study, for a precise investigation of the functional elements in the regulatory region for transcription activation by cAMP-CRP, deletion mutation have been introducted into the regulatory region. The effect of the deletion mutant on transcriptional regulation was tested in vivo by $\beta$-galctosidase activity. Deletion mutants in the regulatory region of glpD demonstrated that the presence of the CRP-binding site resulted in an sixfold increase in promoter activity. And also deletion mutants of glpE gene demonstrated that the presence of the CRP-binding site resulted in an eightfold increase in promoter activity. Insertion of 22 bp oligomer in the deletion mutants has shown that the CRP binding site is need for maximal expression of glpD and glpE genes. glpD and glpE gene, cAMP-CRP complex, deletion mutant, transcriptional regulation.