• The KIPS Transactions:PartD
• /
• v.14D no.1 s.111
• /
• pp.9-20
• /
• 2007

Groups of genes control the functioning of a cell by complex interactions. Such interactions of gene groups are tailed Gene Regulatory Networks(GRNs). Two previous data mining approaches, clustering and classification, have been used to analyze gene expression data. Though these mining tools are useful for determining membership of genes by homology, they don't identify the regulatory relationships among genes found in the same class of molecular actions. Furthermore, we need to understand the mechanism of how genes relate and how they regulate one another. In order to detect regulatory relationships among genes from time-series Microarray data, we propose a novel approach using frequent pattern mining and chain rules. In this approach, we propose a method for transforming gene expression data to make suitable for frequent pattern mining, and gene expression patterns we detected by applying the FP-growth algorithm. Next, we construct a gene regulatory network from frequent gene patterns using chain rules. Finally, we validate our proposed method through our experimental results, which are consistent with published results.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2017.06a
• /
• pp.109-109
• /
• 2017

The core components of ABA-dependent gene expression signaling have been identified in Arabidopsis and rice. This signaling pathway consists of four major components; group A OsbZIPs, SAPKs, subclass A OsPP2Cs and OsPYL/RCARs in rice. These might be able to make thousands of combinations through interaction networks resulting in diverse signaling responses. We tried to characterize those gene functions using transient gene expression for rice protoplasts (TGERP) because it is instantaneous and convenient system. Firstly, in order to monitor the ABA signaling output, we developed reporter system named pRab16A-fLUC which consists of Rab16A promoter of rice and luciferase gene. It responses more rapidly and sensitively to ABA than pABRC3-fLUC that consists of ABRC3 of HVA1 promoter in TGERP. We screened the reporter responses for over-expression of each signaling components from group A OsbZIPs to OsPYL/RCARs with or without ABA in TGERP. OsbZIP46 induced reporter most strongly among OsbZIPs tested in the presence of ABA. SAPKs could activate the OsbZIP46 even in the ABA independence. Subclass A OsPP2C6 and -8 almost completely inhibited the OsbZIP46 activity in the different degree through the SAPK9. Lastly, OsPYL/RCAR2 and -5 rescued the OsbZIP46 activity in the presence of SAPK9 and OsPP2C6 dependent on ABA concentration and expression level. By using TGERP, we could characterize successfully the effects of ABA dependent gene expression signaling components in rice. In conclusion, TGERP represents very useful technology to study systemic functional genomics in rice or other monocots.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.2
• /
• pp.192-197
• /
• 2012

With the advent of DNA microarray technologies, researches for disease diagnosis has been actively in progress. In typical experiments using microarray data, problems such as the large number of genes and the relatively small number of samples, the inherent measurement noise and the heterogeneity across different samples are the cause of the performance decrease. To overcome these problems, a new method using functional modules (e.g. signaling pathways) used as markers was proposed. They use the method using an activity of pathway summarizing values of a member gene's expression values. It showed better classification performance than the existing methods based on individual genes. The activity calculation, however, used in the method has some drawbacks such as a correlation between individual genes and each phenotype is ignored and characteristics of individual genes are removed. In this paper, we propose a method based on the ensemble classifier. It makes weak classifiers based on feature vectors using subsets of genes in selected pathways, and then infers the final classification result by combining the results of each weak classifier. In this process, we improved the performance by minimize the search space through a filtering process using gene-gene interaction information and the mRMR filter. We applied the proposed method to a classifying the lung cancer, it showed competitive classification performance compared to existing methods.

• The KIPS Transactions:PartD
• /
• v.18D no.2
• /
• pp.89-100
• /
• 2011

The CNV (Copy Number Variation) which is one of the genetic structural variations in human genome is closely related with the function of gene. In particular, the genome-wide association studies for genetic diseased persons have been researched. However, there have been few studies which infer the genetic function of CNV with normal human. In this paper, we propose the analysis method to reveal the functional relationship between common CNV and genes without considering their genomic loci. To achieve that, we propose the data integration method for heterogeneity biological data and novel measurement which can calculate the correlation between common CNV and genes. To verify the significance of proposed method, we has experimented several verification tests with GO database. The result showed that the novel measurement had enough significance compared with random test and the proposed method could systematically produce the candidates of genetic function which have strong correlation with common CNV.

• Parasites, Hosts and Diseases
• /
• v.58 no.5
• /
• pp.513-525
• /
• 2020

Clonorchis sinensis is a food-borne trematode that infects more than 15 million people. The liver fluke causes clonorchiasis and chronical cholangitis, and promotes cholangiocarcinoma. The underlying molecular pathogenesis occurring in the bile duct by the infection is little known. In this study, transcriptome profile in the bile ducts infected with C. sinensis were analyzed using microarray methods. Differentially expressed genes (DEGs) were 1,563 and 1,457 at 2 and 4 weeks after infection. Majority of the DEGs were temporally dysregulated at 2 weeks, but 519 DEGs showed monotonically changing expression patterns that formed seven distinct expression profiles. Protein-protein interaction (PPI) analysis of the DEG products revealed 5 sub-networks and 10 key hub proteins while weighted co-expression network analysis (WGCNA)-derived gene-gene interaction exhibited 16 co-expression modules and 13 key hub genes. The DEGs were significantly enriched in 16 Kyoto Encyclopedia of Genes and Genomes pathways, which were related to original systems, cellular process, environmental information processing, and human diseases. This study uncovered a global picture of gene expression profiles in the bile ducts infected with C. sinensis, and provided a set of potent predictive biomarkers for early diagnosis of clonorchiasis.

• Journal of Microbiology and Biotechnology
• /
• v.8 no.4
• /
• pp.378-387
• /
• 1998

The DNA sequence immediately following the xynA gene of Bacillus stearothermophilus 236 ［about l-kb region downstream from the translational termination codon (TAA) of the xynA gene］was found to have an ability to enhance the xylanase activity of the upstream xynA gene. An 849-bp ORF was identified in the downstream region, and the ORF was confirmed to encode a novel protein of 283 amino acids designated as XaiF (xylanase-activity-increasing factor). From the nucleotide sequence of the xaiF gene, the molecular mass and pI of XaiF were deduced to be 32,006 Da and 4.46, respectively. XaiF was overproduced in the E. coli cells from the cloned xaiF gene by using the T7 expression system. The transcriptional initiation site was determined by primer extension analysis and the putative promoter and ribosome binding regions were also identified. Blast search showed that the xaiF and its protein product had no homology with any gene nor any protein reported so far. Also, in B. subtilis, the xaiF trans-activated the xylanase activity at the same rate as in E. coli. In contrast, xaiF had no activating effect on the co-expressed ${\beta}-xylosidase$ of the xylA gene derived from the same strain of B. stearothermophilus. In addition, the intracellular and extracellular fractions from the E. coli cells carrying the plasmid-borne xaiF gene did not increase the isolated xylanase activity, indicating that the protein-protein interaction between XynA and XaiF was not a causative event for the xylanase activating effect of the xaiF gene.

• KSBB Journal
• /
• v.13 no.4
• /
• pp.418-423
• /
• 1998

Cellular transfections with cationic liposomes are widely empolyed for gene and oligonucleotide transfer in vitro because of their safety and ease of use. However, they still suffer from the low transfection efficiency comparing with viral vectors. Substantial effort shave been focused on increasing transfection efficiency by supplementing the liposome/DNA complexes(lipoplex) with various components. In this work, we tired three kinds of supplements, Poly-L-lysine(PLL), transferrin and a mixture of anionic lipids(PS/PE/PC), to study their effects on gene transfer yield and gene expression efficiency. PLL, a polycationic polymer, enhanced gene transfer yield by 3 times but the gene expression efficiency was increased only by 1.5 times. this result implies that PLL can enhance the transfection efficiency mainly by increasing the rate of outermembrane transport of lipoplex into the cells. On the other hand, transferrin which can facilitate the gene transfer via ligand-receptor interaction gave not only increased gene transfer yield but also enhanced gen expression efficiency by 2.8 times. Transferrin seems to contribute to the escape of plasmid from endosomes through ligand-receptor recycle mechanism. When the cells were treated with a mixture of anionic lipids for 3 hours before the transfection, gene transfer yield was slightly decreased but the gene expression efficiency was enhanced by 1.9 times. This is presumably due to the accelerated liposome-plasmid dissociation by the anionic lipids, and the increased delivery of plasmid to the nucleus. According to these results, it is clear that the supplementation to ameliorate transfection efficiency with cationic liposomes should be contrived in the direction of increasing delivery of plasmid.

• KIPS Transactions on Software and Data Engineering
• /
• v.8 no.10
• /
• pp.397-402
• /
• 2019

Accurately predicting cancer prognosis to provide appropriate treatment strategies for patients is one of the critical challenges in bioinformatics. Many researches have suggested machine learning models to predict patients' outcomes based on their gene expression data. Gene expression data is high-dimensional numerical data containing about 17,000 genes, so traditional researches used feature selection or dimensionality reduction approaches to elevate the performance of prognostic prediction models. These approaches, however, have an issue of making it difficult for the predictive models to grasp any biological interaction between the selected genes because feature selection and model training stages are performed independently. In this paper, we propose a novel two-dimensional image formatting approach for gene expression data to achieve feature selection and prognostic prediction effectively. Node2Vec is exploited to integrate biological interaction network and gene expression data and a convolutional neural network learns the integrated two-dimensional gene expression image data and predicts cancer prognosis. We evaluated our proposed model through double cross-validation and confirmed superior prognostic prediction accuracy to traditional machine learning models based on raw gene expression data. As our proposed approach is able to improve prediction models without loss of information caused by feature selection steps, we expect this will contribute to development of personalized medicine.

• Korean Journal of Biological Psychiatry
• /
• v.15 no.1
• /
• pp.29-34
• /
• 2008

Objectives : This study aimed to test potential modifying effects of education on the association between apolipoprotein E ${\varepsilon}4$ (Apo E4) and cognitive decline. Methods : A community cohort(N=683) aged 65 or over completed the Korean version of Mini-Mental State Examination(MMSE-K) at baseline and two years later(1999-2001). Apo E polymorphisms were genotyped, and classified into that with or without Apo E4. Educational levels were categorized into people with or without education. Covariates included demographic(age, gender), life style(smoking, alcohol drinking), clinical (depression, sleep disorder, vascular risk factors) characteristics. Results : The association between Apo E4 and cognitive decline was significant only in the old persons with no education. The interaction term between education and Apo E4 on cognitive decline was significant(p=0.040). Conclusion : Elders with no education might be more vulnerable to the impact of Apo E4 on cognitive decline, which suggests gene-environment interaction.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.5
• /
• pp.1993-1999
• /
• 2014

Background: This study aimed to explore the role of XRCC1 (Arg399Gln) and XPD (Lys751Gln) gene polymorphisms, lifestyle and environmental factors as well as their possible interactions in propensity to develop lung cancer in a population with high incidence from North East India. Materials and Methods: A total of 272 lung cancer cases and 544 controls were collected and XRCC1 (Arg399Gln) and XPD (Lys751Gln) genotypes were analyzed using a polymerase chain reaction based restriction fragment length polymorphism assay. Conditional multiple logistic regression analysis was used to calculate adjusted odds ratios and 95% confidence intervals after adjusting for confounding factors. Results: The combined Gln/Gln genotype of XRCC1 and XPD genes (OR=2.78, CI=1.05-7.38; p=0.040) was significantly associated with increased risk for lung cancer. Interaction of XRCC1Gln/Gln genotype with exposure of wood combustion (OR=2.56, CI=1.16-5.66; p=0.020), exposure of cooking oil fumes (OR=3.45, CI=1.39-8.58; p=0.008) and tobacco smoking (OR=2.54, CI=1.21-5.32; p=0.014) and interaction of XPD with betel quid chewing (OR=2.31, CI=1.23-4.32; p=0.009) and tobacco smoking (OR=2.13, CI=1.12-4.05; p=0.022) were found to be significantly associated with increased risk for lung cancer. Conclusions: Gln/Gln alleles of both XRCC1 and XPD genes appear to amplify the effects of household exposure, smoking and betel quid chewing on lung cancer risk in the study population.