• Journal of Life Science
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• v.19 no.4
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• pp.449-456
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• 2009

Murine Neuro-2a (N2a) cells have been widely used for the investigation of neuronal differentiation, trophic interaction and neurotoxic effects of various compounds and their associated mechanisms. N2a cells have many genomic variations such as gains or losses in DNA copy number, similar to other neuroblastoma cells, and no systematic or high-resolution studies of their genome-wide chromosomal aberrations have been reported. Presently, we conducted a systematic genome-wide determination of chromosomal aberrations in N2a cells using a high-throughput, oligonucleotide array-based comparative genomic hybridization (oaCGH) technique. A hidden Markov Model was employed to assign each genomic oligonucleotide to a DNA copy number state: double loss, single loss, normal, gain, double gain and amplification. Unlike most neuroblastoma cells, Mycn amplification was not observed in N2a cells. In addition, these cells showed gain only in the neuron-derived neurotrophic factor (NF), while other neurotrophic factors such as glial line-derived NF and brain-derived NF presented normal copy numbers. Chromosomes 4, 8, 10, 11 and 15 displayed more than 1000 aberrational oligonucleotides, while chromosomes 3, 17, 18 and 19 displayed less than 20. The largest region of gain was located on chromosome 8 and its size was no less than 26.7 Mb (Chr8:8427841-35162415), while chromosome 4 had the longest region of single deletion, with a size of 15.1 Mb (Chr4:73265785-88374165).

• Journal of KIISE:Software and Applications
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• v.37 no.1
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• pp.1-8
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• 2010

Recently lots of attention has been paid to gene set analysis for identifying differentially expressed gene-sets between two sample groups. Unlike earlier approaches, the gene set analysis enables us to find significant gene-sets along with their functional characteristics. For this reason, various novel approaches have been suggested lately for gene set analysis. As one of such, PAGE is a parametric approach that employs average difference (AD) as an expression metric to quantify expression differences between two sample groups and assumes that the distribution of gene scores is normal. This approach is preferred to non-parametric approach because of more effective performance. However, the metric AD does not reflect either gene expression intensities or variances over samples in calculating gene scores. Thus, in this paper, we investigate the usefulness of several other expression metrics for parametric gene-set analysis, which consider actual expression intensities of genes or their expression variances over samples. For this purpose, we examined three expression metrics, WAD (weighted average difference), FC (Fisher's criterion), and Abs_SNR (Absolute value of signal-to-noise ratio) for parametric gene set analysis and evaluated their experimental results.

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

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.6
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• pp.965-971
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• 2011

As the liver cancer in our country cancerous occurrence frequency to be the gastric cancer in the common cancer, If the case which will be discovered in early rising the treatment record was considered seriously about under the early detection. The system which it sees with the system for the early detection of the liver cancer reacts the blood of the control group other than the patient who is confirmed as the liver cancer and the liver cancer to the biochip and aptamer protein biochip profiles mechanical studying leads and it is a system which it classifies. 1149 each other it reacted blood samples of the control group other than the liver cancer patient who is composed of the total 85 samples and the liver cancer which is composed of 310 samples to the biochip which is composed with different oligo from the present paper and it was a data which it makes acquire worker the neural network it led and it analyzes the classification efficiency of the result 95.38 ~ 97.95% which it was visible.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1079-1094
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• 2014

In this paper, we study efficient gene selection methods by using conditional mutual information. We suggest gene selection methods using conditional mutual information based on semiparametric methods utilizing multivariate normal distribution and Edgeworth approximation. We compare our suggested methods with other methods such as mutual information filter, SVM-RFE, Cai et al. (2009)'s gene selection (MIGS-original) in SVM classification. By these experiments, we show that gene selection methods using conditional mutual information based on semiparametric methods have better performance than mutual information filter. Furthermore, we show that they take far less computing time than Cai et al. (2009)'s gene selection but have similar performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2259-2264
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• 2008

Significant genes are defined as genes in which the expression level characterizes a specific experimental condition. Such genes in which the expression levels differ significantly between different groups are highly informative relevant to the studied phenomenon. In this paper, first the system can detect informative genes by similarity scale combination method being proposed in this paper after normalizing data with methods that are the most widely used among several normalization methods proposed the while. And it compare and analyze a performance of each of normalization methods with multi-perceptron neural network layer. The Result classifying in Multi-Perceptron neural network classifier for selected 200 genes using combination of PC(Pearson correlation coefficient) and ED(Euclidean distance coefficient) after Lowess normalization represented the improved classification performance of 98.84%.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.762-769
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• 2022

Genetic testing in prenatal diagnosis is a precious tool providing valuable information in clinical management and parental decision-making. For the last year, cytogenetic testing methods, such as G-banding karyotype analysis, fluorescent in situ hybridization, chromosomal microarray, and gene panels have evolved to become part of routine laboratory testing. However, the limitations of each of these methods demonstrate the need for a revolutionary technology that can alleviate the need for multiple technologies. The recent introduction of new genomic technologies based on next-generation sequencing has changed the current practice of prenatal testing. The promise of these innovations lies in the fast and cost-effective generation of genome-scale sequence data with exquisite resolution and accuracy for prenatal diagnosis. Here, we review the current state of sequencing-based pediatric diagnostics, associated challenges, as well as future prospects.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.967-970
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• 2008

The liver cancer in our country cancerous occurrence frequency to be the gastric cancer in the common cancer, to initially at second unique condition or symptom after the case which is slowly advanced without gets condition many the case which will be diagnosed in the liver cancer, most there was not a reasonable treatment method especially and if what kind of its treated and convalescence of the patient non quantity one, the case which will be discovered in early rising the treatment record was considered seriously about under the early detection. The system which it sees with the system for the early detection of the liver cancer reacts the blood of the control group other than the patient who is confirmed as the liver cancer and the liver cancer to the bio chip and bio chip Profiles mechanical studying leads and it is a system which it classifies. 1149 each other it reacted blood samples of the control group other than the liver cancer patient who is composed of the total 50 samples and the liver cancer which is composed of 100 samples to the bio chip which is composed with different oligo from the present paper and it was a data which it makes acquire worker the neural network it led and it analyzes the classification efficiency of the result $92{\sim}96%$ which it was visible.

• Horticultural Science & Technology
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• v.33 no.4
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• pp.575-584
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• 2015

Drought stress is a crucial environmental factor determining crop survival and productivity. The goal of this study was to clearly identify a new drought stress-tolerance gene in Brassica rapa. From KBGP-24K microarray data with the B. rapa ssp. pekinensis inbred line 'Chiifu' under drought stress treatment, a gene which was named BrDSR (B. rapa Drought Stress Resistance) was chosen among 738 drought-responsive unigenes. BrDSR function has yet to be determined, but its expression was induced over 6-fold by drought. To characterize BrDSR, the gene was isolated from B. rapa inbred line 'CT001' and found to contain a 438-bp open reading frame encoding a 145 amino acid protein. The full-length cDNA of BrDSR was used to construct an over-expression vector, 'pSL100'. Tobacco transformation was then conducted to analyze whether the BrDSR gene can increase drought tolerance in plants. The BrDSR expression level in T1 transgenic tobacco plants selected via PCR and DNA blot analyses was up to 2.6-fold higher than non-transgenic tobacco. Analysis of phenotype clearly showed that BrDSR-expressing tobacco plants exhibited more tolerance than wild type under 10 d drought stress. Taking all of these findings together, we expect that BrDSR functions effectively in plant growth and survival of drought stress conditions.

• Horticultural Science & Technology
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• v.31 no.6
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• pp.748-755
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• 2013

This study was conducted to find a salt tolerance gene in Brassica rapa. In order to meet this objective, we analyzed data from a KBGP-24K oligo chip [BrEMD (Brassica rapa EST and microarray database)] of the B. rapa ssp. pekinensis 'Chiifu' under salt stress (250 mM NaCl). From the B. rapa KBGP-24K microarray chip analysis, 202 salt-responsive unigenes were primarily selected under salt stress. Of these, a gene with unknown function but known full-length sequence was chosen to closely investigate the gene function. The selected gene was named BrSSR (B. rapa salt stress resistance). BrSSR contains a 285 bp open reading frame encoding a putative 94-amino acid protein, and a DUF581 domain. The pSL94 vector was designed to over-express BrSSR, and was used to transform tobacco plants for salt tolerance analysis. T1 transgenic tobacco plants that over-expressed BrSSR were selected by PCR and DNA blot analyses. Quantitative real-time RT PCR revealed that the expression of BrSSR in transgenic tobacco plants increased by approximately 3.8-fold. Similar results were obtained by RNA blot analysis. Phenotypic characteristics analysis showed that transgenic tobacco plants with over-expressed BrSSR were more salt-tolerant than the wild type control under 250 mM NaCl for 5 days. Based on these results, we hypothesized that the over-expression of BrSSR may be closely related to the enhancement of salt tolerance.