• ETRI Journal
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• v.38 no.1
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• pp.206-215
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• 2016

The detection of gene-gene interactions during genetic studies of common human diseases is important, and the technique of multifactor dimensionality reduction (MDR) has been widely applied to this end. However, this technique is not free from the "curse of dimensionality" -that is, it works well for two- or three-way interactions but requires a long execution time and extensive computing resources to detect, for example, a 10-way interaction. Here, we propose a boosting method to reduce MDR execution time. With the use of pre-evaluation measurements, gene sets with low levels of interaction can be removed prior to the application of MDR. Thus, the problem space is decreased and considerable time can be saved in the execution of MDR.

• Proceedings of the Korea Environmental Mutagen Society Conference
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• 2004.05a
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• pp.19-24
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• 2004

• Proceedings of the Korean Society of Toxicology Conference
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• 2004.05a
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• pp.19-24
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• 2004

• Journal of the Korea Society of Computer and Information
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• v.14 no.5
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• pp.175-182
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• 2009

We extracted protein signal delivery path from protein interaction data, using location information and weight of protein. We obtained the protein interaction data by experimenting in two-hybrid system using Yeast. We simulated function's data of Hypotonic Shock comparing to signal delivery path provided in KEGG from the results. We measured process running period as well. In future, this research can be key to discover the origin of various genetic diseases and develop treatment.

• BMB Reports
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• v.56 no.6
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• pp.321-325
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• 2023

RNAs are pivotal molecules acting as messengers of genetic information and regulatory molecules for cellular development and survival. From birth to death, RNAs face constant cellular decision for the precise control of cellular function and activity. Most eukaryotic cells employ conserved machineries for RNA decay including RNA silencing and RNA quality control (RQC). In plants, RQC monitors endogenous RNAs and degrades aberrant and dysfunctional species, whereas RNA silencing promotes RNA degradation to repress the expression of selected endogenous RNAs or exogenous RNA derived from transgenes and virus. Interestingly, emerging evidences have indicated that RQC and RNA silencing interact with each by sharing target RNAs and regulatory components. Such interaction should be tightly organized for proper cellular survival. However, it is still elusive that how each machinery specifically recognizes target RNAs. In this review, we summarize recent advances on RNA silencing and RQC pathway and discuss potential mechanisms underlying the interaction between the two machineries.

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2003.10a
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• pp.29-29
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• 2003

Incompatible plant-pathogen interactions result in the rapid cell death response known as hypersensitive response (HR) and activation of host defense-related genes. To understand the molecular and cellular mechanism controlling defense response better, several approaches including isolation and characterization of novel genes, promoter analysis of those genes, protein-protein interaction analysis and reverse genetic approach etc. By using the yeast two-hybrid system a clone named Tsipl, Tsil -interacting protein 1, was isolated whose translation product apparently interacted with Tsil, an EREBP/AP2 type DNA binding protein. RNA gel blot analysis showed that the expression of Tsipl was increased by treatment with NaCl, ethylene, salicylic acid, or gibberellic acid. Transient expression analysis using a Tsipl::smGFP fusion gene in Arabidopsis protoplasts indicated that the Tsipl protein was targeted to the outer surface of chloroplasts. The targeted Tsipl::smGFP proteins were diffused to the cytoplasm of protoplasts in the presence of salicylic acid (SA) The PEG-mediated co-transfection analysis showed that Tsipl could interact with Tsil in the nucleus. These results suggest that Tsipl-Tsil interaction might serve to regulate defense-related gene expression. Basically the useful promoters are valuable tools for effective control of gene expression related to various developmental and environmental condition.(중략)

• Genomics & Informatics
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• v.14 no.4
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• pp.166-172
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• 2016

Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still exits limitations in explaining the missing heritability. One approach to solving this missing heritability problem is to investigate gene-gene interactions, rather than a single-locus approach. For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR) method has been widely applied, since the constructive induction algorithm of MDR efficiently reduces high-order dimensions into one dimension by classifying multi-level genotypes into high- and low-risk groups. The MDR method has been extended to various phenotypes and has been improved to provide a significance test for gene-gene interactions. In this paper, we propose a simple method, called accelerated failure time (AFT) UM-MDR, in which the idea of a unified model-based MDR is extended to the survival phenotype by incorporating AFT-MDR into the classification step. The proposed AFT UM-MDR method is compared with AFT-MDR through simulation studies, and a short discussion is given.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.3
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• pp.172-179
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• 2006

Over the past few years, a considerable number of studies have been conducted on modeling the bargaining game using artificial agents on within-model interaction. However, very few attempts have been made at study on between-model interaction. This paper investigates the interaction and co-evolutionary process among heterogeneous artificial agents in the bargaining game. We present two kinds of the artificial agents participating in the bargaining game. They play some bargaining games with their strategies based on genetic algorithm (GA) and reinforcement learning (RL). We compare agents' performance between two agents under various conditions which are the changes of the parameters of artificial agents and the maximal number of round in the bargaining game. Finally, we discuss which agents show better performance and why the results are produced.

• Journal of Microbiology and Biotechnology
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• v.24 no.2
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• pp.217-224
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• 2014

Chicken are considered as the most important source of human infection by Campylobacter jejuni, which primarily arises from contaminated poultry meats. However, the genes expressed in vivo of the interaction between chicken and C. jejuni have not been screened. In this regard, in vivo-induced antigen technology (IVIAT) was applied to identify expressed genes in vivo during interaction between chicken and C. jejuni, a prevalent foodborne pathogen worldwide. Chicken sera were obtained by inoculating C. jejuni NCTC 11168 into Leghorn chickens through oral and intramuscular administration. Pooled chicken sera, adsorbed against in vitro-grown cultures of C. jejuni, were used to screen the inducible expression library of genomic proteins from sequenced C. jejuni NCTC 11168. Finally, 28 unique genes expressed in vivo were successfully identified after secondary and tertiary screenings with IVIAT. The genes were implicated in metabolism, molecular biosynthesis, genetic information processing, transport, regulation and other processes, in addition to Cj0092, with unknown function. Several potential virulence-associated genes were found to be expressed in vivo, including chuA, flgS, cheA, rplA, and Cj0190c. We selected four genes with different functions to compare their expression levels in vivo and in vitro using real-time RT-PCR. The results indicated that these selected genes were significantly upregulated in vivo but not in vitro. In short, the expressed genes in vivo may act as potential virulence-associated genes, the protein encoded by which may be meaningful vaccine candidate antigens for campylobacteriosis. IVIAT provides an important and efficient strategy for understanding the interaction mechanisms between Campylobacter and hosts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2286-2309
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• 2016

Overlay networks have been widely deployed upon the Internet by Service Providers (SPs) to provide improved network services. However, the interaction between each overlay and traffic engineering (TE) as well as the interaction among co-existing overlays may occur. In this paper, we adopt both non-cooperative and cooperative game theory to analyze these interactions, which are collectively called hybrid interaction. Firstly, we model a situation of the hybrid interaction as an n+1-player non-cooperative game, in which overlays and TE are of equal status, and prove the existence of Nash equilibrium (NE) for this game. Secondly, we model another situation of the hybrid interaction as a 1-leader-n-follower Stackelberg-Nash game, in which TE is the leader and co-existing overlays are followers, and prove that the cost at Stackelberg-Nash equilibrium (SNE) is at least as good as that at NE for TE. Thirdly, we propose a cooperative coalition mechanism based on Shapley value to overcome the inherent inefficiency of NE and SNE, in which players can improve their performance and form stable coalitions. Finally, we apply distinct genetic algorithms (GA) to calculate the values for NE, SNE and the assigned cost for each player in each coalition, respectively. Analytical results are confirmed by the simulation on complex network topologies.