• Asian Pacific Journal of Cancer Prevention
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• v.16 no.12
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• pp.5005-5006
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• 2015

Gastric cancer as one of the most common cancers worldwide has various genetic and environmental risk factors including Helicobacter pylori (H.pylori) infection. Recently, loss of a tumor suppressor gene named promyelocytic leukemia (PML) has been identified in gastric cancer. However, no mutation has been found in this gene in gastric cancer samples. Cag A H.pylori protein has been shown to exert post transcriptional regulation of some tumor suppressor genes. In order to assess such a mechanism for PML degradation, we performed in silico analyses to establish any interaction between PML and Cag A proteins. In silico interaction and docking studies showed that these two proteins may have stable interactions. In addition, we showed that imatinib kinase inhibitor can restore PML function by inhibition of casein kinase 2.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.837-840
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• 2014

Interactions between genes have long been recognized and studied by many researchers, and they formed a large-scale interaction networks. In systems biology, it has been a challenge to investigate the factors to determine network dynamics. Here, we create a new network called an effectiveness network by calculating thy dynamical effectiveness from a node to another node. We found that robust nodes tend to have smaller number of edges than non-robust nodes. This implies that hub nodes are likely to affect the network robustness.

• Journal of KIISE:Software and Applications
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• v.31 no.12
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• pp.1602-1610
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• 2004

As various genome projects have produced enormous amount of biosequence data, functional sequence analysis in terms of tile nucleic acid and protein becomes very significant. In functional genomics and proteomics, the functional analysis of each individual gene and protein remains a big challenge. Contrary to traditional studies, which regard proteins as not components of a whole protein interaction network but individual entities, recent studies have focused on examining functions and roles of each individual gene and protein in view of a whole life system. In this regard, it has been recognized as an appropriate method to analyze protein function on the basis of synthetic information of its interaction and domain modularity. In this context, this paper introduces the PIVS (Protein-protein interaction Inference & Visualization System), which predicts the interaction relationship of input proteins by taking advantage of information on homology degree, domain modules which input sequences contain, and protein interaction relationship. The information on domain modules can increase the accuracy of the function and interaction relationship analysis in terms of the specificity and sensitivity.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.7
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• pp.2745-2749
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• 2015

Objective: To study the PLCE1 gene rs2274223 polymorphism with regard to esophageal cancer and its interaction with diet, lifestyle, psychological and environmental factors in Southwest Shandong province. Materials and Methods: A case series study (case-case) was conducted. Questionnaire data were collected and 3 ml-5ml venous blood was drawn for DNA extraction among the qualified research subjects. PLCE1 gene polymorphism was detected after PCR amplification of DNA. SPSS 13.0 software was used for statistical analysis of the data. Results: The three genotypes A/A, A/G and G/G PLCE1 gene rs2274223 was 31, 16 and 4 cases, accounting for 60.8%, 31.4%, 0.08% respectively. The difference of three genotypes (AA/GA/GG) proportion between negative and positive family history of patients was statistically significant, ${\chi}^2=6.213$, p=0.045. There was no statistically significant relationship between PLCE1 gene rs2274223 polymorphism and smoking, drinking, ${\chi}^2=0.119$, p=0.998, and ${\chi}^2=1.727$, p=0.786. There was no linkage of the three rs2274223 PLCE1 gene genotypes (AA/GA/GG) proportion with eating fried, pickled, hot, mildew, overnight, smoked, excitant food, eat speed, salt taste or not (p>0.05). or with living environment pollution and nine risk factors of occupational exposure (p>0.05). There was no statistically significant difference in TS scores between different genotype of rs2274223 PLCE1 gene. Conclusions: The PLCE1 rs2274223 polymorphism has a relationship with family history of esophageal cancer, but does not have any significant association with age, gender, smoking, alcohol drinking, food hygiene, eating habits, living around the environment and occupation in cases.

• The Korean Journal of Physiology and Pharmacology
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• v.24 no.1
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• pp.53-68
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• 2020

The purpose of this study was to characterize the genetic contribution to endothelial adaptation to exercise training. Vasoreactivity was assessed in aortas from four inbred mouse strains (129S1, B6, NON, and SJL) after 4 weeks of moderate intensity continuous exercise training (MOD), high intensity interval training (HIT) or in sedentary controls (SED). Intrinsic variations in endothelium-dependent vasorelaxation (EDR) to acetylcholine (ACh) as well as vasocontractile responses were observed across SED groups. For responses to exercise training, there was a significant interaction between mouse strain and training intensity on EDR. Exercise training had no effect on EDR in aortas from 129S1 and B6 mice. In NON, EDR was improved in aortas from MOD and HIT compared with respective SED, accompanied by diminished responses to PE in those groups. Interestingly, EDR was impaired in aorta from SJL HIT compared with SED. The transcriptional activation of endothelial genes was also influenced by the interaction between mouse strain and training intensity. The number of genes altered by HIT was greater than MOD, and there was little overlap between genes altered by HIT and MOD. HIT was associated with gene pathways for inflammatory responses. NON MOD genes showed enrichment for vessel growth pathways. These findings indicate that exercise training has non-uniform effects on endothelial function and transcriptional activation of endothelial genes depending on the interaction between genetic background and training intensity.

• Proceedings of the Korean Society of Applied Pharmacology
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• 2008.04a
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• pp.77-86
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• 2008

It's been known that overexpression of the oncoprotein Her2 (eu/ErbB2), transmembrane receptor protein, occurs in human breast cancer. Her2-positive breast cancer patients who have Her2 overexpression show less therapeutic efficacy with enhanced metathesis and increased resistance to chemotherapy. So far, a humanized monoclonal antibody against Her2 protein called Herceptin is the only drug approved by Food and Drug Administration for treatment of Her2-overexpressing breast tumors. However, antibody therapy of Herceptin may not be ideal method for therapeutic intervention of Her2 protein expression. The therapeutic intervention of Her2 protein expression may be more efficiently achieved by inhibiting the expression of Her2 gene rather than by down-regulating the Her2 protein already overexpressed. Here, we found that the interaction of two proteins of ESX (an epithelial-restricted transcription factor) and DRIP130/CRSP130/Sur2 (a Ras-linked subunit of human mediator complexes) mediates the expression of Her2 gene. The association of ESX with Sur2 is mediated by a small hydrophobic face of 8-amino acid helix in ESX, suggesting that the ESX-Sur2 interaction can be a new novel target for Her2-positive cancer. The process to develop potent ESX-Sur2 interaction inhibitors targeting for Her2-positive cancer therapeutics will be discussed.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.861-869
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• 2011

One of the main objects of recent genetic studies is to understand genetic factors that induce complex diseases. If there are interactions between loci, it is difficult to find such associations through a single-locus analysis strategy. Thus we need to consider the gene-gene interactions and/or gene-environment interactions. The MDR(multifactor dimensionality reduction) method is being used frequently; however, it is not appropriate to detect interactions caused by a small fraction of the possible genotype pairs. In this study, we propose a relative risk interaction explorer that detects interactions through the calculation of the relative risks between the control and disease groups from each genetic combinations. For illustration, we apply this method to MDR open source data. We also compare the MDR and the proposed method using the simulated data eight genetic models.

• Genomics & Informatics
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• v.20 no.3
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• pp.26.1-26.19
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• 2022

Diabetes and its related complications are associated with long term damage and failure of various organ systems. The microvascular complications of diabetes considered in this study are diabetic retinopathy, diabetic neuropathy, and diabetic nephropathy. The aim is to identify the weighted co-expressed and differentially expressed genes (DEGs), major pathways, and their miRNA, transcription factors (TFs) and drugs interacting in all the three conditions. The primary goal is to identify vital DEGs in all the three conditions. The overlapped five genes (AKT1, NFKB1, MAPK3, PDPK1, and TNF) from the DEGs and the co-expressed genes were defined as key genes, which differentially expressed in all the three cases. Then the protein-protein interaction network and gene set linkage analysis (GSLA) of key genes was performed. GSLA, gene ontology, and pathway enrichment analysis of the key genes elucidates nine major pathways in diabetes. Subsequently, we constructed the miRNA-gene and transcription factor-gene regulatory network of the five gene of interest in the nine major pathways were studied. hsa-mir-34a-5p, a major miRNA that interacted with all the five genes. RELA, FOXO3, PDX1, and SREBF1 were the TFs interacting with the major five gene of interest. Finally, drug-gene interaction network elucidates five potential drugs to treat the genes of interest. This research reveals biomarker genes, miRNA, TFs, and therapeutic drugs in the key signaling pathways, which may help us, understand the processes of all three secondary microvascular problems and aid in disease detection and management.

• Proceedings of the Botanical Society of Korea Conference
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• 1999.07a
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• pp.21-35
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• 1999

We have previously isolated OsMADS4 gene that is a member of the class B MADS box genes from rice. In this study, another member of the class B MADS box genes was isolated from rice flower by the yeast two-hybrid screening method using OsMADS4 as bait. RNA blot analyses revealed that the clone, OsMADS16, was expressed in the second and third whorls, whereas the OsMADS4 transcripts were present in the second, third, and fourth whorls. These expression patterns of the OsMADS16 and OsMADS4 genes are very similar with those of AP3 and PI, the class B genes of Arabidopsis, respectively. In the yeast two-hybrid system, OsMADS4 interacted only with OsMADS16 among several rice MADS genes investigated, suggesting that OsMADS4 and OsMADS16 function as a heterodimer in specifying sepal and petal identities. We have also isolated OsMADS6 gene using OsMADS1 as a probe. Both are members of the AGL2 MADS family. Various MADS genes that encode for protein-protein interaction partners of the OsMADS6 protein were isolated by the yeast two-hybrid screening method. A majority of these genes belong to the AGL2 family. Sequence Homology, expression pattern, and ectopic expression phenotypes indicated that one of the interaction partners, OsMADS14, appears to be homologous to API, the class A MADS gene of Arabidopsis.

• Genes and Genomics
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• v.40 no.12
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• pp.1363-1371
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• 2018

One of the main concerns in biology is extracting sophisticated features from DNA sequence for gene interaction determination, receiving a great deal of researchers' attention. The epigenetic modifications along with their patterns have been intensely recognized as dominant features affecting on gene expression. However, studying sequenced-based features highly correlated to this key element has remained limited. The main objective in this research was to propose a new feature highly correlated to epigenetic modifications capable of classification of genes. In this paper, classification of 34 genes in PPAR signaling pathway associated with muscle fat tissue in human was performed. Using different statistical outlier detection methods, we proposed that 5-mers highly correlated to epigenetic modifications can correctly categorize the genes involved in the same biological pathway or process. Thirty-four genes in PPAR signaling pathway were classified via applying a proposed feature, 5-mers strongly associated to 17 different epigenetic modifications. For this, diverse statistical outlier detection methods were applied to specify the group of thoroughly correlated genes. The results indicated that these 5-mers can appropriately identify correlated genes. In addition, our results corresponded to GeneMania interaction information, leading to support the suggested method. The appealing findings imply that not only epigenetic modifications but also their highly correlated 5-mers can be applied for reconstructing gene regulatory networks as supplementary data as well as other applications like physical interaction, genes prioritization, indicating some sort of data fusion in this analysis.