• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.225-243
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• 2016

Thanks to recent advance of next generation sequencing techniques, RNA-seq enabled to have an unprecedented opportunity to identify transcript variants with isoform diversity and allelic imbalance (Anders et al., 2012) by different transcriptional rates. To date, it is well known that those features might be associated with the aberrant patterns of disease complexity such as tissue (Anders and Huber, 2010; Anders et al., 2012; Nariai et al., 2014) specific differential expression at isoform levels or tissue specific allelic imbalance in mal-functionality of disease processes, etc. Nevertheless, the knowledge of post-transcriptional modification and AI in transcriptomic and genomic areas has been little known in the traditional platforms due to the limitation of technology and insufficient resolution. We here stress the potential of isoform variability and allelic specific expression that are relevant to the abnormality of disease mechanisms in transcriptional genetic regulatory networks. In addition, we systematically review how robust Bayesian approaches in RNA-seq have been developed and utilized in this regard in the field.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.7
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• pp.2793-2800
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• 2015

In molecular-targeted cancer therapy, acquired resistance to gemcitabine is a major clinical problem that reduces its effectiveness, resulting in recurrence and metastasis of cancers. In spite of great efforts to reveal the overall mechanism of acquired gemcitabine resistance, no definitive genetic factors have been identified that are absolutely responsible for the resistance process. Therefore, we performed a cross-platform meta-analysis of three publically available microarray datasets for cancer cell lines with acquired gemcitabine resistance, using the R-based RankProd algorithm, and were able to identify a total of 158 differentially expressed genes (DEGs; 76 up- and 82 down-regulated) that are potentially involved in acquired resistance to gemcitabine. Indeed, the top 20 up- and down-regulated DEGs are largely associated with a common process of carcinogenesis in many cells. For the top 50 up- and down-regulated DEGs, we conducted integrated analyses of a gene regulatory network, a gene co-expression network, and a protein-protein interaction network. The identified DEGs were functionally enriched via Gene Ontology hierarchy and Kyoto Encyclopedia of Genes and Genomes pathway analyses. By systemic combinational analysis of the three molecular networks, we could condense the total number of DEGs to final seven genes. Notably, GJA1, LEF1, and CCND2 were contained within the lists of the top 20 up- or down-regulated DEGs. Our study represents a comprehensive overview of the gene expression patterns associated with acquired gemcitabine resistance and theoretical support for further clinical therapeutic studies.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.197-201
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• 2005

When we want to find out the regulatory relationships between genes from gene expression data, dimensionality is one of the big problem. In general, the size of search space in modeling the regulatory relationships grows in O(n$^2$) while the number of genes is increasing. However, hopefully it can be reduced to O(kn) with selected k by applying divide and conquer heuristics which depend on some assumptions about genetic network. In this paper, we approach the modeling problem in divide-and-conquer manner. We applied clustering to make the problem into small sub-problems, then hierarchical model process is applied to those small sub-problems.

• Journal of Microbiology and Biotechnology
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• v.16 no.11
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• pp.1661-1677
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• 2006

Rhizobium and related genera are soil bacteria with great metabolic plasticity. These microorganisms survive in many different environments and are capable of eliciting the formation of nitrogen-fixing nodules on legumes. The successful establishment of symbiosis is precisely regulated and requires a series of signal exchanges between the two partners. Quorum sensing (QS) is a prevalent form of population density-dependent gene regulation. Recently, increasing evidence indicates that rhizobial quorum sensing provides a pervasive regulatory network, which plays a more generalized role in the physiological activity of free-living rhizobia, as well as during symbiosis. Several rhizobia utilize multiple, overlapping quorum sensing systems to regulate diverse properties, including conjugal transfer and copy number control of plasmids, exopolysaccharide biosynthesis, rhizosphere-related functions, and cell growth. Genomic and proteomic analyses have begun to reveal the wide range of functions under quorum-sensing control.

• Bioinformatics and Biosystems
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• v.2 no.2
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• pp.52-57
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• 2007

The computational discovery of transcription factor binding site is one of the important tools in the genetic and genomic analysis. Rough prediction of gene regulation network and finding possible co-regulated genes are typical applications of the technique. Countless motif-discovery algorithms have been proposed for the past years. However, there is no dominant algorithm yet. Each algorithm does not give enough accuracy without extensive information. In this paper, we explore the possibility of combining multiple algorithms for the one integrated result in order to improve the performance and the convenience of researchers. Moreover, we apply new high order information that is reorganized from the set of basis predictions to the final prediction.

• Journal of Life Science
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• v.26 no.8
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• pp.904-910
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• 2016

Complex traits are determined by the combined effects of many loci and are affected by gene networks or biological pathways. Systems biology approaches have an important role in the identification of candidate genes related to complex diseases or traits at the system level. The gene network analysis has been performed by diverse types of methods such as gene co-expression, gene regulatory relationships, protein-protein interaction (PPI) and genetic networks. Moreover, the network-based methods were described for predicting gene functions such as graph theoretic method, neighborhood counting based methods and weighted function. However, there are a limited number of researches in livestock. The present study systemically analyzed genes associated with 102 types of economic traits based on the Animal Trait Ontology (ATO) and identified their relationships based on the gene co-expression network and PPI network in cattle. Then, we constructed the two types of gene network databases and network visualization system (http://www.nabc.go.kr/cg). We used a gene co-expression network analysis from the bovine expression value of bovine genes to generate gene co-expression network. PPI network was constructed from Human protein reference database based on the orthologous relationship between human and cattle. Finally, candidate genes and their network relationships were identified in each trait. They were typologically centered with large degree and betweenness centrality (BC) value in the gene network. The ontle program was applied to generate the database and to visualize the gene network results. This information would serve as valuable resources for exploiting genomic functions that influence economically and agriculturally important traits in cattle.

• Genomics & Informatics
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• v.12 no.4
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• pp.181-186
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• 2014

Genome-wide association studies have proven the highly polygenic architecture of complex diseases or traits; therefore, single-locus-based methods are usually unable to detect all involved loci, especially when individual loci exert small effects. Moreover, the majority of associated single-nucleotide polymorphisms resides in non-coding regions, making it difficult to understand their phenotypic contribution. In this work, we studied epistatic interactions associated with three common diseases using Korea Association Resource (KARE) data: type 2 diabetes mellitus (DM), hypertension (HT), and coronary artery disease (CAD). We showed that epistatic single-nucleotide polymorphisms (SNPs) were enriched in enhancers, as well as in DNase I footprints (the Encyclopedia of DNA Elements [ENCODE] Project Consortium 2012), which suggested that the disruption of the regulatory regions where transcription factors bind may be involved in the disease mechanism. Accordingly, to identify the genes affected by the SNPs, we employed whole-genome multiple-cell-type enhancer data which discovered using DNase I profiles and Cap Analysis Gene Expression (CAGE). Assigned genes were significantly enriched in known disease associated gene sets, which were explored based on the literature, suggesting that this approach is useful for detecting relevant affected genes. In our knowledge-based epistatic network, the three diseases share many associated genes and are also closely related with each other through many epistatic interactions. These findings elucidate the genetic basis of the close relationship between DM, HT, and CAD.

• IMMUNE NETWORK
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• v.16 no.3
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• pp.176-182
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• 2016

CCR3 is a chemokine receptor that mediates the accumulation of allergic inflammatory cells, including eosinophils and Th2 cells, at inflamed sites. The regulatory sequence of the CCR3 gene, contains two Runt-related transcription factor (RUNX) 1 sites and two PU.1 sites, in addition to a functional GATA site for transactivation of the CCR3 gene. In the present study, we examined the effects of the cis-acting elements of RUNX1 and PU.1 on transcription of the gene in EoL-1 eosinophilic cells and Jurkat T cells, both of which expressed functional surface CCR3 and these two transcription factors. Introduction of RUNX1 siRNA or PU.1 siRNA resulted in a modest decrease in CCR3 reporter activity in both cell types, compared with transfection of GATA-1 siRNA. Cotransfection of the two siRNAs led to inhibition in an additive manner. EMSA analysis showed that RUNX1, in particular, bound to its binding motifs. Mutagenesis analysis revealed that all point mutants lacking RUNX1- and PU.1-binding sites exhibited reduced reporter activities. These results suggest that RUNX1 and PU.1 participate in transcriptional regulation of the CCR3 gene.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.10
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• pp.1481-1492
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• 2012

The interaction of the genes involved in intestinal development is the molecular basis of the regulatory mechanisms of intestinal development. The objective of this study was to identify the significant pathways and key genes that regulate intestinal development in Landrace piglets, and elucidate their rules of operation. The differential expression of genes related to intestinal development during suckling time was investigated using a porcine genome array. Time sequence profiles were analyzed for the differentially expressed genes to obtain significant expression profiles. Subsequently, the most significant profiles were assayed using Gene Ontology categories, pathway analysis, network analysis, and analysis of gene co-expression to unveil the main biological processes, the significant pathways, and the effective genes, respectively. In addition, quantitative real-time PCR was carried out to verify the reliability of the results of the analysis of the array. The results showed that more than 8000 differential expression transcripts were identified using microarray technology. Among the 30 significant obtained model profiles, profiles 66 and 13 were the most significant. Analysis of profiles 66 and 13 indicated that they were mainly involved in immunity, metabolism, and cell division or proliferation. Among the most effective genes in these two profiles, CN161469, which is similar to methylcrotonoyl-Coenzyme A carboxylase 2 (beta), and U89949.1, which encodes a folate binding protein, had a crucial influence on the co-expression network.

• Journal of Life Science
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• v.8 no.3
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• pp.263-271
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• 1998

One of the better-characterized transcription factor of E. coli is the cAMP receptor protein(CRP) and the CRP binds cAMP and DNA. The cAMP-CRP complex is involved in regulation of many genes at bacteria. The cAMP-CRP regulatory element represents, in some respects, a global regulatory network. The aim of this work was to study the structure and the mechanisms controlling the expression of CRP in Serratia marcescens. We have been get 5 different clones from Serratia which stimulated the cells to use maltose as a sole carbon source in E. coli TP2139. The crp gene clone, pCKB12, was confirmed by Southern hybridization with E. coli crp gene. The location of the crp gene was determined by construction subclones carrying various portions of pCKB12. To investigate the potential role of CRP in E. coli, lacZ fused plasmids were constructed and investigated the ${\beta}$-galactosidase activity of the fused plasmid. The Serratiamarcescens cAMP receptor protein can substitute the E. coli CRP in transcriptional activation at the lacZ gene. These results suggest that Serratia marcescens cAMP receptor protein complex functions to regulate several promoters in E. coli.