• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.339-343
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• 2005

Boolean networks(BN) construction is one of the commonly used methods for building gene networks from time series microarray data. However, BN has two major drawbacks. First, it requires heavy computing times. Second, the binary transformation of the microarray data may cause a loss of information. This paper propose two methods using liner regression to construct gene regulatory networks. The first proposed method uses regression based BN variable selection method, which reduces the computing time significantly in the BN construction. The second method is the regression based network method that can flexibly incorporate the interaction of the genes using continuous gene expression data. We construct the network structure from the simulated data to compare the computing times between Boolean networks and the proposed method. The regression based network method is evaluated using a microarray data of cell cycle in Caulobacter crescentus.

• IMMUNE NETWORK
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• v.10 no.6
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• pp.247-249
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• 2010

Foxp3 is a transcript factor for regulatory T cell development. Interestingly, Foxp3-expressing cells were identified in B cells, especially in CD19(+)CD5(+) B cells, while those were not examined in CD19(+)CD5(-) B cells. Foxp3-expressing CD5(+) B cells in this study were identified in human PBMCs and were found to consist of $8.5{\pm}3.5%$ of CD19(+)CD5(+) B cells. CD19(+)CD5(+)Foxp3(+) B cells showed spontaneous apoptosis. Rare CD19(+)CD5(+) Foxp3(+) regulatory B cell (Breg) population was unveiled in human peripheral blood mononuclear cells and suggested as possible regulatory B cells (Breg) as regulatory T cells (Treg). The immunologic and the clinical relevant of Breg needs to be further investigated.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6631-6636
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• 2013

Through years of effort, researchers have made notable progress in gene and microRNA fields about retinoblastoma morbidity. However, experimentally validated data for genes, microRNAs (miRNAs) and transcription factors (TFs) can only be found in a scattered form, which makes it difficult to conclude the relationship between genes and retinoblastoma systematically. In this study, we regarded genes, miRNAs and TFs as elements in the regulatory network and focused on the relationship between pairs of examples. In this way, we paid attention to all the elements macroscopically, instead of only researching one or several. To show regulatory relationships over genes, miRNAs and TFs clearly, we constructed 3 regulatory networks hierarchically, including a differentially expressed network, a related network and a global network, for analysis of similarities and comparison of differences. After construction of the three networks, important pathways were highlighted. We constructed an upstream and downstream element table of differentially expressed genes and miRNAs, in which we found self-adaption relations and circle-regulation. Our study systematically assessed factors in the pathogenesis of retinoblastoma and provided theoretical foundations for gene therapy researchers. In future studies, especial attention should be paid to the highlighted genes and miRNAs.

• IMMUNE NETWORK
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• v.9 no.6
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• pp.209-235
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• 2009

There has been an explosion of literature focusing on the role of regulatory T (Treg) cells in cancer immunity. It is becoming increasingly clear that Treg cells play an active and significant role in the progression of cancer, and have an important role in suppressing tumor-specific immunity. Thus, there is a clear rationale for developing clinical strategies to diminish their regulatory influences, with the ultimate goal of augmenting antitimor immunity. Therefore, manipulation of Treg cells represent new strategies for cancer treatment. In this Review, I will summarize and review the explosive recent studies demonstrating that Treg cells are increased in patients with malignancies and restoration of antitumor immunity in mice and humans by depletion or reduction of Treg cells. In addition, I will discuss both the prognostic value of Treg cells in tumor progression in tumor-bearing hosts and the rationale for strategies for therapeutic vaccination and immunotherapeutic targeting of Treg cells with drugs and microRNA.

• Genomics & Informatics
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• v.19 no.2
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• pp.16.1-16.14
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• 2021

Even in the current age of advanced medicine, the prognosis of malignant peritoneal mesothelioma (MPM) remains abysmal. Molecular mechanisms responsible for the initiation and progression of MPM are still largely not understood. Adopting an integrated bioinformatics approach, this study aims to identify the key genes and pathways responsible for MPM. Genes that are differentially expressed in MPM in comparison with the peritoneum of healthy controls have been identified by analyzing a microarray gene expression dataset. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses of these differentially expressed genes (DEG) were conducted to gain a better insight. A protein-protein interaction (PPI) network of the proteins encoded by the DEGs was constructed using STRING and hub genes were detected analyzing this network. Next, the transcription factors and miRNAs that have possible regulatory roles on the hub genes were detected. Finally, survival analyses based on the hub genes were conducted using the GEPIA2 web server. Six hundred six genes were found to be differentially expressed in MPM; 133 are upregulated and 473 are downregulated. Analyzing the STRING generated PPI network, six dense modules and 12 hub genes were identified. Fifteen transcription factors and 10 miRNAs were identified to have the most extensive regulatory functions on the DEGs. Through bioinformatics analyses, this work provides an insight into the potential genes and pathways involved in MPM.

• Proceedings of the Microbiological Society of Korea Conference
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• 2009.05a
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• pp.109-109
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• 2009

• The Korea Genome Conference
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• 2004.07a
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• pp.35.2-35.2
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• 2004

• Proceedings of the Zoological Society Korea Conference
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• 2003.08a
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• pp.55-55
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• 2003

No Abstract, See Full Text

• Proceedings of the Microbiological Society of Korea Conference
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• 2006.05a
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• pp.82-83
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• 2006

• Korean Journal of Radiology
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• v.24 no.3
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• pp.247-258
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• 2023

Objective: To localize the neuroanatomical substrate of rapid eye movement sleep behavior disorder (RBD) and to investigate the neuroanatomical locational relationship between RBD and α-synucleinopathy neurodegenerative diseases. Materials and Methods: Using a systematic PubMed search, we identified 19 patients with lesions in different brain regions that caused RBD. First, lesion network mapping was applied to confirm whether the lesion locations causing RBD corresponded to a common brain network. Second, the literature-based RBD lesion network map was validated using neuroimaging findings and locations of brain pathologies at post-mortem in patients with idiopathic RBD (iRBD) who were identified by independent systematic literature search using PubMed. Finally, we assessed the locational relationship between the sites of pathological alterations at the preclinical stage in α-synucleinopathy neurodegenerative diseases and the brain network for RBD. Results: The lesion network mapping showed lesions causing RBD to be localized to a common brain network defined by connectivity to the pons (including the locus coeruleus, dorsal raphe nucleus, central superior nucleus, and ventrolateral periaqueductal gray), regardless of the lesion location. The positive regions in the pons were replicated by the neuroimaging findings in an independent group of patients with iRBD and it coincided with the reported pathological alterations at post-mortem in patients with iRBD. Furthermore, all brain pathological sites at preclinical stages (Braak stages 1-2) in Parkinson's disease (PD) and at brainstem Lewy body disease in dementia with Lewy bodies (DLB) were involved in the brain network identified for RBD. Conclusion: The brain network defined by connectivity to positive pons regions might be the regulatory network loop inducing RBD in humans. In addition, our results suggested that the underlying cause of high phenoconversion rate from iRBD to neurodegenerative α-synucleinopathy might be pathological changes in the preclinical stage of α-synucleinopathy located at the regulatory network loop of RBD.