• 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.

• 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.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.427-430
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• 2005

Studies on cellular pathways and networks are now one of the most actively researched topics in all fields of biomedicine ranging from developmental biology to etiology. Many databases have been developed and quantitative simulation models have been proposed. One of the eventual goals of pathway/network studies is to integrate different types of pathway/network models and databases to simulate overall cellular responses. A bottleneck to this goal is modeling gene expression since the mechanism of this process is not yet fully unveiled. We are developing a small scale computer program called CiRMU (Cis-Regulatory Machinery Unit model) for describing, viewing, analyzing, and modeling the process of gene expression. A prototype system is being designed and implemented for analyzing functions of nuclear receptors.

• 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.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.9
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• pp.3677-3683
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• 2015

Abnormally expressed microRNAs (miRNAs) and genes have been found to play key roles in esophageal squamous cell carcinoma (ESCC), but little is known about the underlying mechanisms. The aim of this paper was to assess inter-relationships and the regulatory mechanisms of ESCC through a network-based approach. We built three regulatory networks: an abnormally expressed network, a related network and a global network. Unlike previous examples, containing information only on genes or miRNAs, the prime focus was on relationships. It is worth noting that abnormally expressed network emerged as a fault map of ESCC. Theoretically, ESCC might be treated and prevented by correcting the included errors. In addition, the predicted transcription factors (TFs) obtained by the P-match method also warrant further study. Our results may further guide gene therapy researchers in the study of ESCC.

• Microbiology and Biotechnology Letters
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• v.49 no.4
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• pp.478-484
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• 2021

Cellular resources including transcriptional and translational machineries in bacteria are limited, yet microorganisms depend upon them to maximize cellular fitness. Bacteria have evolved strategies for using resources economically. Regulatory networks for the gene expression system enable the cell to synthesize proteins only when necessary. At the same time, regulatory interactions enable the cell to limit losses when the system cannot make a cellular profit due to fake substrates. Also, the architecture of the gene expression flow can be advantageous for clustering functionally related products, thus resulting in effective interactions among molecules. In addition, cellular systems modulate the investment of proteomes, depending upon nutrient qualities, and fast-growing cells spend more resources on the synthesis of ribosomes, whereas nonribosomal proteins are synthesized in nutrient-limited conditions. A deeper understanding of cellular mechanisms underlying the optimal allocation of cellular resources can be used for biotechnological purposes, such as designing complex genetic circuits and constructing microbial cell factories.

• Korean Journal of Environmental Biology
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• v.26 no.4
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• pp.377-384
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• 2008

A cell is the product of a long period of evolution and can be represented as an optimized system (homeostasis). Stimuli from the outside environment are received by sensory apparatus on the surface of the cell and transferred through complicated pathways and eventually regulate gene expression. These signals affect cell physiology, growth, and development, and the interaction among genes in the signal transduction pathway is a critical part of the regulation. In this study, the interactions of deletion mutants and overexpression of the extracopies of the genes were used to understand their relationships to each other. Also, green fluorescent protein (GFP reporter gene) was fused to the regulatory genes to elucidate their interactions. Cooverexpression of the two genes in extracopy plasmids suggested that patS acts at the downstream of hetR in the regulatory network. The experiments using gfp fusion in different genetic background cells also indicated the epistasis relationships between the two genes. A model describing the regulatory network that controls cell development is presented.

• Genomics & Informatics
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• v.19 no.4
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• pp.42.1-42.17
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• 2021

Salivary gland carcinoma (SGC) is rare cancer, constituting 6% of neoplasms in the head and neck area. The most responsible genes and pathways involved in the pathology of this disorder have not been fully understood. We aimed to identify differentially expressed genes (DEGs), the most critical hub genes, transcription factors, signaling pathways, and biological processes (BPs) associated with the pathogenesis of primary SGC. The mRNA dataset GSE153283 in the Gene Expression Omnibus database was re-analyzed for determining DEGs in cancer tissue of patients with primary SGC compared to the adjacent normal tissue (adjusted p-value < 0.001; |Log2 fold change| > 1). A protein interaction map (PIM) was built, and the main modules within the network were identified and focused on the different pathways and BP analyses. The hub genes of PIM were discovered, and their associated gene regulatory network was built to determine the master regulators involved in the pathogenesis of primary SGC. A total of 137 genes were found to be differentially expressed in primary SGC. The most significant pathways and BPs that were deregulated in the primary disease condition were associated with the cell cycle and fibroblast proliferation procedures. TP53, EGF, FN1, NOTCH1, EZH2, COL1A1, SPP1, CDKN2A, WNT5A, PDGFRB, CCNB1, and H2AFX were demonstrated to be the most critical genes linked with the primary SGC. SPIB, FOXM1, and POLR2A significantly regulate all the hub genes. This study illustrated several hub genes and their master regulators that might be appropriate targets for the therapeutic aims of primary SGC.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.39-49
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• 2004

When there is a lack of detailed kinetic information, dFBA(dynamic flux balance analysis) has correctly predicted cellular behavior under given environmental conditions with FBA and different ial equations. However, until now, dFBA has centered on substrate concentration, cell growth, and gene on/off, but a detailed hierarchical structure of a regulatory network has not been taken into account. For this reason, the dFBA has limited the represen tation of interactions between specific regulatory proteins and genes and the whole transcriptional regulation mechanism with environmental change. Moreover, to calculate optimal metabolic flux distribution which maximizes the growth flux and predict the b ehavior of cell system, linear programming package(LINDO) and spreadsheet package(EXCEL) have been used simultaneously. thses two software package have limited in the visual representation of simulation results and it can be difficult for a user to look at the effects of changing inputs to the models. Here, we descirbes the construction of hierarchical regulatory network with defined symbolsand the development of an integrated system that can predict the total control mechanism of regulatory elements (opero ns, genes, effectors, etc.), substrate concentration, growth rate, and optimal flux distribution with time. All programming procedures were accoplished in a visual programming environment (LabVIEW).

• IMMUNE NETWORK
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• v.11 no.5
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• pp.227-244
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• 2011

MicroRNAs (miRNAs) are small noncoding RNA molecules that negatively regulate gene expression via degradation or translational repression of their target messenger RNAs (mRNAs). Recent studies have clearly demonstrated that miRNAs play critical roles in several biologic processes, including cell cycle, differentiation, cell development, cell growth, and apoptosis and that miRNAs are highly expressed in regulatory T (Treg) cells and a wide range of miRNAs are involved in the regulation of immunity and in the prevention of autoimmunity. It has been increasingly reported that miRNAs are associated with various human diseases like autoimmune disease, skin disease, neurological disease and psychiatric disease. Recently, the identification of miRNAs in skin has added a new dimension in the regulatory network and attracted significant interest in this novel layer of gene regulation. Although miRNA research in the field of dermatology is still relatively new, miRNAs have been the subject of much dermatological interest in skin morphogenesis and in regulating angiogenesis. In addition, miRNAs are moving rapidly center stage as key regulators of neuronal development and function in addition to important contributions to neurodegenerative disorder. Moreover, there is now compelling evidence that dysregulation of miRNA networks is implicated in the development and onset of human neruodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, Huntington's disease, Tourette's syndrome, Down syndrome, depression and schizophrenia. In this review, I briefly summarize the current studies about the roles of miRNAs in various autoimmune diseases, skin diseases, psychoneurological disorders and mental stress.