• Genomics & Informatics
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• v.4 no.2
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• pp.57-64
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• 2006

We identified differentially expressed genes in RAW264.7 cells in response to single and double ligand treatments (LPS, $IFN{\gamma}$, 2MA, LPS plus $IFN{\gamma}$, and LPS plus 2MA). The majority of the regulated transcripts responded additively to dual ligand treatment. However, a significant fraction responded in a non-additive fashion. Several cytokines showing non-additive transcriptional responses to dual ligand treatment also showed non-additive protein production/secretion responses in separately performed experiments. Many of the genes with non-additive responses to LPS plus 2MA showed enhanced responses and encoded pro-inflammatory proteins. LPS plus $IFN{\gamma}$ appeared to induce both non-additive enhancement and non-additive attenuation of gene expression. The affected genes were associated with a variety of biological functions. These experiments reveal both dependent and independent regulatory pathways and point out the specific nature of the regulatory interactions.

• 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).

• Mycobiology
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• v.37 no.3
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• pp.171-182
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• 2009

Many aspergilli that belongs to ascomycetes have sexuality. In a homothallic or self-fertile fungus, a number of fruiting bodies or cleistothecia are formed in a thallus grown from a single haploid conidia or ascospores. Genome-sequencing project revealed that two mating genes (MAT) encoding the regulatory proteins that are necessary for controlling partner recognition in heterothallic fungi were conserved in most aspergilli. The MAT gene products in some self-fertile species were not required for recognition of mating partner at pheromone-signaling stage but required at later stages of sexual development. Various environmental factors such as nutritional status, culture conditions and several stresses, influence the decision or progression of sexual reproduction. A large number of genes are expected to be involved in sexual development of Emericella nidulans (anamorph: Aspergillus nidulans), a genetic and biological model organism in aspergilli. The sexual development process can be grouped into several development stages, including the decision of sexual reproductive cycle, mating process, growth of fruiting body, karyogamy followed by meiosis, and sporulation process. Complicated regulatory networks, such as signal transduction pathways and gene expression controls, may work in each stage and stage-to-stage linkages. In this review, the components joining in the regulatory pathways of sexual development, although they constitute only a small part of the whole regulatory networks, are briefly mentioned. Some of them control sexual development positively and some do negatively. Regarding the difficulties for studying sexual differentiation compare to asexual one, recent progresses in molecular genetics of E. nidulans enlarge the boundaries of understanding sexual development in the non-fertile species as well as in fertile fungi.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.849-852
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• 2014

Reverse engineering of gene regulatory network is a challenging task in computational biology. To detect a regulatory relationship among genes from time series data is called reverse engineering. Reverse engineering helps to discover the architecture of the underlying gene regulatory network. Besides, it insights into the disease process, biological process and drug discovery. There are many statistical approaches available for reverse engineering of gene regulatory network. In our paper, we propose pairwise mutual information for the reverse engineering of a gene regulatory network from time series data. Firstly, we create random boolean networks by the well-known $Erd{\ddot{o}}s-R{\acute{e}}nyi$ model. Secondly, we generate artificial time series data from that network. Then, we calculate pairwise mutual information for predicting the network. We implement of our system on java platform. To visualize the random boolean network graphically we use cytoscape plugins 2.8.0.

• KSBB Journal
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• v.24 no.3
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• pp.259-266
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• 2009

AfsR2 in Streptomyces lividans, a 63-amino acid protein with limited sequence homology to Streptomyces sigma factors, has been known for a global regulatory protein stimulating multiple antibiotic biosynthetic pathways. Although the detailed regulatory mechanism of AfsK-AfsR-AfsR2 system has been well characterized, very little information about the AfsR2-dependent down-stream regulatory genes were characterized. Recently, the null mutant of afsS in S. coelicolor (the identical ortholog of afsR2) has been characterized through DNA microarray system, revealing that afsS deletion regulated several genes involved in antibiotic biosynthesis as well as phosphate-starvation. Through comparative DNA microarray analysis of afsR2-overexpressed S. lividans, here we also identify several afsR2-dependent genes involved in phosphate starvation, morphological differentiation, and antibiotic regulation in S. lividans, confirming that the AfsR2 plays an important pleiotrophic regulatory role in Streptomyces species.

• 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.

• Genomics & Informatics
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• v.21 no.3
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• pp.36.1-36.19
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• 2023

The LIM domain-containing proteins are dominantly found in plants and play a significant role in various biological processes such as gene transcription as well as actin cytoskeletal organization. Nevertheless, genome-wide identification as well as functional analysis of the LIM gene family have not yet been reported in the economically important plant sorghum (Sorghum bicolor L.). Therefore, we conducted an in silico identification and characterization of LIM genes in S. bicolor genome using integrated bioinformatics approaches. Based on phylogenetic tree analysis and conserved domain, we identified five LIM genes in S. bicolor (SbLIM) genome corresponding to Arabidopsis LIM (AtLIM) genes. The conserved domain, motif as well as gene structure analyses of the SbLIM gene family showed the similarity within the SbLIM and AtLIM members. The gene ontology (GO) enrichment study revealed that the candidate LIM genes are directly involved in cytoskeletal organization and various other important biological as well as molecular pathways. Some important families of regulating transcription factors such as ERF, MYB, WRKY, NAC, bZIP, C2H2, Dof, and G2-like were detected by analyzing their interaction network with identified SbLIM genes. The cis-acting regulatory elements related to predicted SbLIM genes were identified as responsive to light, hormones, stress, and other functions. The present study will provide valuable useful information about LIM genes in sorghum which would pave the way for the future study of functional pathways of candidate SbLIM genes as well as their regulatory factors in wet-lab experiments.

• Journal of Plant Biotechnology
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• v.45 no.3
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• pp.183-189
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• 2018

The plant hormone auxin regulates the overall metabolic processes essential for plant growth and development. Auxin signaling is mediated by early auxin response genes, which are classified into three major families: AUXIN/INDOLE ACETIC ACID (AUX/IAA), GRETCHEN HAGEN3 (GH3) and SMALL AUIN UP RNA (SAUR). The SAUR gene family is the largest family among early auxin response genes and encodes the small and highly unstable gene products. The functional roles of SAUR genes have remained unclear for many years. The traditional genetic and molecular studies on the SAUR functions have been hampered by their likely genetic redundancy and tandem arrays of highly related genes in the plant genome, together with the molecular characteristics of SAUR. However, recent studies have suggested possible roles of SAUR in a variety of tissues and developmental stages in accordance with the novel approaches such as gain-of-function and RNA silencing techniques. In this review, the recent research progress on the functional roles and regulatory mechanisms of SAUR and a set of possible future works are discussed.

• Proceedings of the Korean Society for Applied Microbiology Conference
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• 2003.06a
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• pp.63-68
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• 2003

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.4
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• pp.1477-1482
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• 2012

Squamous cell carcinoma and adenocarcinoma are the major histological types of non-small cell lung cancer. Because they differ on the basis of histopathological and clinical characteristics and their relationship with smoking, their etiologies may be different; for example, different tumor suppressor genes may be related to the genesis of each type. We used microarray data to construct three regulatory networks to identify potential genes related to lung adenocarcinoma and squamous cell carcinoma and investigated the similarity and specificity of them. In the network, some of the observed transcription factors and target genes had been previously proven to be related to lung adenocarcinoma and squamous cell carcinoma. We also found some new transcription factors and target genes related to SCC. The results demonstrated that regulatory network analysis is useful in connection analysis between lung adenocarcinoma and squamous cell carcinoma.