• Proceedings of the Korean Society for Bioinformatics Conference
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• 2001.08a
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• pp.103-127
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• 2001

Gene expression studies require statistical experimental designs and validation before laboratory confirmation. Various clustering approaches, such as hierarchical, Kmeans, SOM are commonly used for unsupervised learning in gene expression data. Several classification methods, such as gene voting, SVM, or discriminant analysis are used for supervised lerning, where well-defined response classification is possible. Estimating gene-condition interaction effects require advanced, computationally-intensive statistical approaches.

• Journal of Korean Neurosurgical Society
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• v.66 no.4
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• pp.409-417
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• 2023

Objective : The association between boule (BOLL) and endothelin receptor type A (EDNRA) loci and intracranial aneurysm (IA) formation has been reported via genome-wide association studies. We sought to identify genome-wide interactions involving BOLL and EDNRA loci for IA in a Korean adult cohort. Methods : Genome-wide pairwise interaction analyses of BOLL and EDNRA involving 250 patients with IA and 296 controls were performed using the additive effect model after adjusting for confounding factors. Results : Among 512575 single-nucleotide polymorphisms (SNPs), 23 and 11 common SNPs suggested a genome-wide interaction threshold (p<1.25×10^-8) involving rs700651 (BOLL) and rs6841581 (EDNRA). Rather than singe SNP effect of BOLL or EDNRA on IA development, they showed a synergistic effect on IA formation via multifactorial pair-wise interactions. The rs1105980 of PTCH1 gene showed the most significant interaction with rs700651 (natural log-transformed odds ratio [lnOR], 1.53; p=6.41×10^-11). The rs74585958 of RYK gene interacted strongly with rs6841581 (lnOR, -19.91; p=1.64×10^-9). Although, there was no direct interaction between BOLL and EDNRA variants, two EDNRA-interacting gene variants of TNIK (rs11925024 and rs1231) and FTO (rs9302654), and one BOLL-interacting METTL4 gene variant (rs549315) exhibited marginal interaction with BOLL gene. Conclusion : BOLL or EDNRA may have a synergistic effect on IA formation via multifactorial pair-wise interactions.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.313-318
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• 2005

Estimating the reliability of protein-protein interaction data sets obtained by high-throughput technologies such as yeast two-hybrid assays and mass spectrometry is of great importance. We develop a maximum likelihood estimation method that uses both protein localization and gene expression data to estimate the reliability of protein interaction data sets. By integrating protein localization data and gene expression data, we can obtain more accurate estimates of the reliability of various interaction data sets. We apply the method to protein physical interaction data sets and protein complex data sets. The reliability of the yeast two-hybrid interactions by Ito et al. (2001) is 27%, and that by Uetz et at.(2000) is 68%. The reliability of the protein complex data sets using tandem affinity purification-mass spec-trometry (TAP) by Gavin et at. (2002) is 45%, and that using high-throughput mass spectrometric protein complex identification (HMS-PCI) by Ho et al. (2002) is 20%. The method is general and can be applied to analyze any protein interaction data sets.

• Genomics & Informatics
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• v.10 no.4
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• pp.256-262
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• 2012

Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene ($G{\times}G$) interactions. However, the biological interpretation of $G{\times}G$ interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified $G{\times}G$ interactions. The proposed network graph analysis consists of three steps. The first step is for performing $G{\times}G$ interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified $G{\times}G$ interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform $G{\times}G$ interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified $G{\times}G$ interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of $G{\times}G$ interactions.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.5
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• pp.1803-1808
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• 2012

This study aimed to investigate the effects of Ser/Cys polymorphism in hOGG1 gene, Arg/Pro polymorphism in p53 gene, smoking and their interactions on the development of lung cancer. Ser/Cys polymorphism in hOGG1 and Arg/Pro polymorphism in p53 among 124 patients with lung cancer and 128 normal people were detected using PCR-RFLP. At the same time, smoking status was investigated between the two groups. Logistic regression was used to estimate the effects of Ser/Cys polymorphism and Arg/Pro polymorphisms, smoking and their interactions on the development of lung cancer. ORs (95% CI) of smoking, hOGG1 Cys/Cys and p53 Pro/Pro genotypes were 2.34 (1.41-3.88), 2.12 (1.03-4.39), and 2.12 (1.15-3.94), respectively. The interaction model of smoking and Cys/Cys was super-multiplicative or multiplicative, and the OR (95% CI) for their interaction item was 1.67 (0.36 -7.78). The interaction model of smoking and Pro/Pro was super-multiplicative with an OR (95%CI) of their interaction item of 5.03 (1.26-20.1). The interaction model of Pro/Pro and Cys/Cys was multiplicative and the OR (95%CI) of their interaction item was 0.99 (0.19-5.28). Smoking, hOGG1 Cys/Cys, p53 Pro/Pro and their interactions may be the important factors leading to the development of lung cancer.

• Journal of Plant Biotechnology
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• v.32 no.2
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• pp.73-83
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• 2005

Disease resistance in plants is often controlled by gene-for-gene mechanism in which avirulence (avr) gene products encoding by pathogens are specifically recognized, either directly or indirectly by plant disease resistance (R) gene products and sequential signal transduction pathways activating defense responses are rapidly triggered. As a results, not only exhibit a resistance against invading pathogens but also plants maintain the systemic acquired resistance (SAR) to various other pathogens. This molecular interaction between pathogen and plant is commonly compared to innate immune system of animal. Recent studies arising from molecular characterization of a number of R genes from various plant species that confer resistance to different pathogens and corresponding avr genes from various pathogens resulted in the accumulation of a wealth of knowledge on molecular mechanism of gene-for-gene interaction. Furthermore, new technologies of genomics and proteomics make it possible to monitor the genome-wide gene regulation and protein modification during activation of disease resistance, expanding our ability to understand the plant immune response and develop new crops resistant to biotic stress.

• Animal cells and systems
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• v.8
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• pp.51-51
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• 2004

• The Journal of Natural Sciences
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• v.9 no.1
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• pp.25-29
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• 1997

To study the mechanism of lipocortin-1, the 37 kDa protein, one of the annxin superfamily thought to be a second messenger during the Glucocorticoid dependent anti-inflammatory action, the gene for lipocortin-1 binding protein was isolated using the yeast two hybrid assay, the yeast based genetic assay recognizing the protein-protein interaction. The results showed that this gene has a weak homology to the for the human serine proteinase.

• Journal of Microbiology and Biotechnology
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• v.17 no.2
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• pp.359-363
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• 2007

Because of the importance of the type III protein-secretion system in bacteria-plant interaction, its function in bacterial pathogenesis of plants has been intensively studied. To identity bacterial proteins interacting with Xanthomonas hrp gene products that are involved in pathogenicity, we performed the glutathione-bead binding analysis of Xanthomonas lysates containing GST-tagged Hrp proteins. Analysis of glutathione-bead bound proteins by 1-DE and MALDI-TOF has demonstrated that Avr proteins, RecA, and several components of the type III secretion system interact with HrpB protein. This proteomic approach could provide a powerful tool in finding interaction partners of Hrp proteins whose roles in host-pathogen interaction need further studies.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1331-1339
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• 2013

The lipoprotein lipase (LPL) gene can be considered a functional candidate gene that regulates fatty acid composition. Oh etc (2013) investigated the relationship between unsaturated fatty acids and five novel SNPs, and had confirmed that three polymorphic SNPs (c.322G>A, c.329A>T and c.1591G>A) were associated with fatty acid composition. We have used generalized linear model for adjusted environmental effects and multifactor dimensionality reduction (MDR) method to identify gene-gene interaction effect of statistical model in general. We applied the MDR method on the identify major interaction effects of exonic single nucleotide polymorphisms (SNPs) in the LPL gene for economic traits in Korean cattles population.