• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.164-169
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• 2003

In this paper, we propose the integrated Bayesian network framework to reconstruct genetic regulatory networks from genome expression data. The proposed model overcomes the dimensionality problem of multivariate analysis by building coherent sub-networks from confined gene clusters and combining these networks via intermediary points. Gene Shaving algorithm is used to cluster genes that share a common function or co-regulation. Retrieved clusters incorporate prior biological knowledge such as Gene Ontology, pathway, and protein protein interaction information for extracting other related genes. With these extended gene list, system builds genetic sub-networks using Bayesian network with MDL score and Sparse Candidate algorithm. Identifying functional modules of genes is done by not only microarray data itself but also well-proved biological knowledge. This integrated approach can improve there liability of a network in that false relations due to the lack of data can be reduced. Another advantage is the decreased computational complexity by constrained gene sets. To evaluate the proposed system, S. Cerevisiae cell cycle data [1] is applied. The result analysis presents new hypotheses about novel genetic interactions as well as typical relationships known by previous researches [2].

• Applied Biological Chemistry
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• v.41 no.3
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• pp.224-227
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• 1998

The expression of ferritin involved in iron metabolism is regulated at the translational level by the interaction of iron regulatory protein with iron-responsive element(IRE) in the 5'-untranslated region of ferritin transcript. To identify the role of structural element utilized for translational regulation of ferritin, we studied the effects of mutations in the ferritin IRE by measuring IRP binding activity and translational activity. Our data suggest that the cytosine at bulged position of IRE within ferritin is important for the formation of RNA secondary structure involved in translational regulation.

• BMB Reports
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• v.46 no.1
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• pp.41-46
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• 2013

Identifying genes indispensable for an organism's life and their characteristics is one of the central questions in current biological research, and hence it would be helpful to develop computational approaches towards the prediction of essential genes. The performance of a predictor is usually measured by the area under the receiver operating characteristic curve (AUC). We propose a novel method by implementing genetic algorithms to maximize the partial AUC that is restricted to a specific interval of lower false positive rate (FPR), the region relevant to follow-up experimental validation. Our predictor uses various features based on sequence information, protein-protein interaction network topology, and gene expression profiles. A feature selection wrapper was developed to alleviate the over-fitting problem and to weigh each feature's relevance to prediction. We evaluated our method using the proteome of budding yeast. Our implementation of genetic algorithms maximizing the partial AUC below 0.05 or 0.10 of FPR outperformed other popular classification methods.

• Biomedical Science Letters
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• v.26 no.3
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• pp.238-243
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• 2020

Tuberculosis is a global public health problem and manifests itself as a difference in the genetic susceptibility of the host, along with the properties of Mycobacterium tuberculosis (MTB). The single nucleotide polymorphisms (SNPs) and candidate genes proposed in the Genome-wide association study (GWAS) on tuberculosis in a recently published Chinese population were reported. In this study, we investigated whether the genetic polymorphism of candidate genes related to tuberculosis is reproduced when targeting Koreans. The CLCN6 (rs12404124, rs198391, rs535107), DOK7 (rs1203104, rs1203103) and HLA-DRA (rs1051336) gene polymorphisms showed statistically significant results. In addition, it was also found whether it acts as an expression quantitative trait loci (eQTL) that can influence gene expression. This study confirmed that the genetic polymorphism of the three genes (CLCN6, DOK7, HLA-DRA) affects the development of tuberculosis and will help to understand the genetic specificity of tuberculosis and the interaction between pathogens and hosts.

• Molecules and Cells
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• v.37 no.9
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• pp.691-698
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• 2014

SCYL1-BP1 is thought to function in the p53 pathway through Mdm2 and hPirh2, and mutations in SCYL1-BP1 are associated with premature aging syndromes such as Geroderma Osteodysplasticum; however, these mechanisms are unclear. Here, we report significant alterations in miRNA expression levels when SCYL1-BP1 expression was inhibited by RNA interference in HEK293T cells. We functionally characterized the effects of potential kernel miRNA-target genes by miRNA-target network and protein-protein interaction network analysis. Importantly, we showed the diminished SCYL1-BP1 dramatically reduced the expression levels of EEA1, BMPR2 and BRCA2 in HEK293T cells. Thus, we infer that SCYL1-BP1 plays a critical function in HEK293T cell development and directly regulates miRNA-target genes, including, but not limited to, EEA1, BMPR2, and BRCA2, suggesting a new strategy for investigating the molecular mechanism of SCYL1-BP1.

• The Plant Pathology Journal
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• v.27 no.1
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• pp.26-32
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• 2011

Plant-pathogenic bacteria including Xanthomonas spp. carry genetic diversity in composition of avirulence genes for interaction with their host plants. Previously, we reported genetic diversity of avirulence genes in X. axonopodis pv. glycines. In this study, we determined genetic diversity of five avirulence genes, avrBs1, avrBs2, avrBs3, avrBs4, and avrRxv, in three other Xanthomonas species isolated in Korea by genomic southern hybridization. Although Korean races of X. campestris pv. vesicatoria that were isolated from year 1995 to 2002 had the same avirulence gene patterns as those that already reported, there was race shift from race 3 to race 1 by acquisition of avrBs3 genes. X. campestris pv. campestris isolated from Chinese cabbage, but not from cabbage or radish, carried two avrBs3 genes, and one of them affected HR-eliciting ability of this bacterium in broccoli. X. oryzae pv. oryzae carried eight to thirteen avrBs3 gene homologs, and this bacterium showed dynamic changes of resistance patterns in rice probably by losing or obtaining avrBs3 genes. These results indicate that avrBs3 gene is more diverse in Xanthomonas spp. than other four avirulence genes and also host ranges of these bacteria can be easily changed by loss or acquisition of avrBs3 genes.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1089-1102
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• 2017

In software systems, it has been observed that a fault is often caused by an interaction between a small number of input parameters. Even for moderately sized software systems, exhaustive testing is practically impossible to achieve. This is either due to time or cost constraints. Combinatorial (t-way) testing provides a technique to select a subset of exhaustive test cases covering all of the t-way interactions, without much of a loss to the fault detection capability. In this paper, an approach is proposed to generate 2-way (pairwise) test sets using genetic algorithms. The performance of the algorithm is improved by creating an initial solution using the overlap coefficient (a similarity matrix). Two mutation strategies have also been modified to improve their efficiency. Furthermore, the mutation operator is improved by using a combination of three mutation strategies. A comparative survey of the techniques to generate t-way test sets using genetic algorithms was also conducted. It has been shown experimentally that the proposed approach generates faster results by achieving higher percentage coverage in a fewer number of generations. Additionally, the size of the mixed covering arrays was reduced in one of the six benchmark problems examined.

• Genomics & Informatics
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• v.20 no.1
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• pp.8.1-8.14
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• 2022

Despite the success of recent genome-wide association studies investigating longitudinal traits, a large fraction of overall heritability remains unexplained. This suggests that some of the missing heritability may be accounted for by gene-gene and gene-time/environment interactions. In this paper, we develop a Bayesian variable selection method for longitudinal genetic data based on mixed models. The method jointly models the main effects and interactions of all candidate genetic variants and non-genetic factors and has higher statistical power than previous approaches. To account for the within-subject dependence structure, we propose a grid-based approach that models only one fixed-dimensional covariance matrix, which is thus applicable to data where subjects have different numbers of time points. We provide the theoretical basis of our Bayesian method and then illustrate its performance using data from the 1000 Genome Project with various simulation settings. Several simulation studies show that our multivariate method increases the statistical power compared to the corresponding univariate method and can detect gene-time/ environment interactions well. We further evaluate our method with different numbers of individuals, variants, and causal variants, as well as different trait-heritability, and conclude that our method performs reasonably well with various simulation settings.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.2
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• pp.160-165
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• 2007

Dispersion parameters for the number of piglets born alive were estimated using a repeatability and random regression model. Six sow breeds/lines were included in the analysis: Swedish Landrace, Large White and both crossbred lines between them, German Landrace and their cross with Large White. Fixed part of the model included sow genotype, mating season as month-year interaction, parity and weaning to conception interval as class effects. The age at farrowing was modelled as a quadratic regression nested within parity. The previous lactation length was fitted as a linear regression. Random regressions for parity on Legendre polynomials were included for direct additive genetic, permanent environmental, and common litter environmental effects. Orthogonal Legendre polynomials from the linear to the cubic power were fitted. In the repeatability model estimate of heritability was 0.07, permanent environmental effect as ratio was 0.04, and common litter environmental effect as ratio was 0.01. Estimates of genetic parameters with the random regression model were generally higher than in the repeatability model, except for the common litter environmental effect. Estimates of heritability ranged from 0.06 to 0.10. Permanent environmental effect as a ratio increased along a trajectory from 0.03 to 0.11. Magnitudes of common litter effect were small (around 0.01). The eigenvalues of covariance functions showed that between 7 and 8 % of genetic variability was explained by individual genetic curves of sows. This proportion was mainly covered by linear and quadratic coefficients. Results suggest that the random regression model could be used for genetic analysis of litter size.

• BMB Reports
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• v.39 no.1
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• pp.105-110
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• 2006

We have screened 766 strains of fungi from the BIOTEC Culture Collection (BCC) for xylanases working in extreme pH and/or high temperature conditions, the so-called extreme xylanases. From a total number of 32 strains producing extreme xylanases, the strain BCC7928, identified by using the internal transcribed spacer (ITS) sequence of rRNA to be a Marasmius sp., was chosen for further characterization because of its high xylanolytic activity at temperature as high as $90^{\circ}C$. The crude enzyme possessed high thermostability and pH stability. Purification of this xylanase was carried out using an anion exchanger followed by hydrophobic interaction chromatography, yielding the enzyme with >90% homogeneity. The molecular mass of the enzyme was approximately 40 kDa. The purified enzyme retained broad working pH range of 4-8 and optimal temperature of $90^{\circ}C$. When using xylan from birchwood as substrate, it exhibits $K_m$ and $V_{max}$ values of $2.6{\pm}0.6\;mg/ml$ and $428{\pm}26\;U/mg$, respectively. The enzyme rapidly hydrolysed xylans from birchwood, beechwood, and exhibited lower activity on xylan from wheatbran, or celluloses from carboxymethylcellulose and Avicel. The purified enzyme was highly stable at temperature ranges from 50 to $70^{\circ}C$. It retained 84% of its maximal activity after incubation in standard buffer containing 1% xylan substrate at $70^{\circ}C$ for 3 h. This thermostable xylanase should therefore be useful for several industrial applications, such as agricultural, food and biofuel.