• Korean Journal of Clinical Laboratory Science
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• v.56 no.1
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• pp.10-20
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• 2024

RNA-sequencing (RNA-seq) is a technique used for providing global patterns of transcriptomes in samples. However, it can only provide the average gene expression across cells and does not address the heterogeneity within the samples. The advances in single-cell RNA sequencing (scRNA-seq) technology have revolutionized our understanding of heterogeneity and the dynamics of gene expression at the single-cell level. For example, scRNA-seq allows us to identify the cell types in complex tissues, which can provide information regarding the alteration of the cell population by perturbations, such as genetic modification. Since its initial introduction, scRNA-seq has rapidly become popular, leading to the development of a huge number of bioinformatic tools. However, the analysis of the big dataset generated from scRNA-seq requires a general understanding of the preprocessing of the dataset and a variety of analytical techniques. Here, we present an overview of the workflow involved in analyzing the scRNA-seq dataset. First, we describe the preprocessing of the dataset, including quality control, normalization, and dimensionality reduction. Then, we introduce the downstream analysis provided with the most commonly used computational packages. This review aims to provide a workflow guideline for new researchers interested in this field.

• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.277-287
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• 2013

It is important to detect the gene-gene interaction in GWAS (genome-wide association study). There have been many studies on detecting gene-gene interaction. The one is D-MDR (dummy multifoactor dimensionality reduction) method. The goal of this study is to evaluate the power of D-MDR for identifying gene-gene interaction by simulation. Also we applied the method on the identify interaction effects of single nucleotide polymorphisms (SNPs) responsible for economic traits in a Korean cattle population (real data).

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1271-1280
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• 2010

We have used multifactor dimensionality reduction (MDR) method to study genegene interaction effect of statistical model in general. But, MDR method could not be applied in the continuous data. In this paper, continuous-type data by the support vector machine (SVM) algorithm are proposed to the MDR method which provides an introduction to the technique. Also we apply the method on the identify major interaction effects of single nucleotide polymorphisms (SNPs) responsible for economic traits in a Korean cattle population.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.7
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• pp.1429-1436
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• 2009

In this paper, we propose a robust eye detection method using template matching based on genetic algorithm in the single facial image. The previous works for detecting pupil using genetic algorithm had a problem that the detection accuracy is influnced much by the initial population for it's random value. Therefore, their detection result is not consistent. In order to overcome this point we extract local minima in the facial image and generate initial populations using ones that have high fitness with a template. Each chromosome consists of geometrical informations for the template image. Eye position is detected by template matching. Experiment results verify that the proposed eye detection method improve the precision rate and high accuracy in the single facial image.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.3
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• pp.65-74
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• 2005

본 연구는 기계고장 시 대체경로를 고려한 새로운 유사계수와 주어진 기간 내 수요변화를 고려하여 제조 셀을 구성하는 방법론을 개발하는 것이다. 본 연구의 방법론은 2단계로 나누어진다. 1단계에서는 기계고장 시 이용 가능한 대체경로를 고려하여 새로운 유사계수를 제시하고 유전자 알고리즘을 활용하여 부품 군을 식별하는 것이다. 셀 응용의 성패를 좌우하는 주요한 요소들 중 하나는 수요변화에 대한 유연성으로 수요변화, 이용 가능한 기계의 능력 및 납기일에 따라 셀을 재구성하기가 쉬운 일은 아닐 것이다. 대부분의 논문에서 제안한 방법들은 단일기간에 대한 고정 수요를 고려하였으나, 수요의 변화로 인하여 셀 설계는 대부분의 연구에서 고려한 단일기간보다는 장기적인 면을 고려해야 할 것이다. 수요가 변화하는 상황에서 운용요소와 일정요소를 고려한 셀 구성에 대한 새로운 방법론을 2단계에 소개한다.

• Journal of the Korean Data and Information Science Society
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• v.21 no.3
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• pp.387-395
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• 2010

It is important to identify the interaction of genes about human disease and characteristic value. Many studies as like logistic analysis, have associated being pursued, but, previous methods did not consider the sub-group of the genotypes. So, QTL interactions and the GMM (genotype matrix mapping) have been developed. In this study, we detect the superior genotype combination to have an impact on economic traits of Korean cattle based on the study over GMM method. Thus, we identified interaction effects of single nucleotide polymorphisms (SNPs) responsible for average daily gain(ADG), marbling score (MS), carcass cold weight (CWT), longissimus muscle dorsiarea (LMA) using GMM method. In addition, we examine significance of the major genotype combination selected by implementing permutation test of the F-measure which was not obtained by Sachiko et al.

• Journal of the Korean Chemical Society
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• v.50 no.2
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• pp.116-122
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• 2006

In this study we extracted DNA from 100 tissues of breast cancer patients and 103 normals. Then we confirmed single-nucleotide polymorphism(SNP) using PCR-DHPLC(polymerase chain reaction-denaturing high performance liquid chromatogrphy).Also, we studied SNP of samples using several columns to identify relation between packing materials of column and resolution.As a result, we identified 4 C/A, C/G genotypes(4%) in exon 5 and 37 T del genotypes(37%) in exon 8 among 100 breast cancer tissues and 2 in exon 5, 9 in exon 8 among 103 normal samples.In resolution test, we confirmed that PS-DVB(poly styrene-divinylbenzen) column is more efficient than C18 column.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1385-1395
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• 2014

Economic traits of livestock are affected by environmental factors and genetic factors. In addition, it is not affected by one gene, but is affected by interaction of genes. We used a linear regression model in order to adjust environmental factors. And, in order to identify gene-gene interaction effect, we applied data mining techniques such as neural network, logistic regression, CART and C5.0 using five-SNPs (single nucleotide polymorphism) of FASN (fatty acid synthase). We divided total data into training (60%) and testing (40%) data, and applied the model which was designed by training data to testing data. By the comparison of prediction accuracy, C5.0 was identified as the best model. It were selected superior genotype using the decision tree.

• Journal of Animal Science and Technology
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• v.53 no.5
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• pp.389-395
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• 2011

This study was conducted to investigate the combined effect of fatty acid synthase (FASN) and Acetyl CoA Carboxylase-${\alpha}$ (ACACA) genes on carcass traits of Korean cattle (Hanwoo). A total of 1,057 commercial Hanwoo cattle provided by the NongHyup Livestock Research Center (NLRC) and Hanwoo Performance Competition (HPC) were used to analyze the effect of four single nucleotide polymorphisms (SNPs) within FASN (g.11280A>G, g.16024A>G, g.16039T>C, and g.17924A>G) and one SNP within ACACA (g.2274G>A) genes. In addition, the effect of genotypic combinations between FASN (g.17924A>G) and ACACA (g.2274G>A) SNPs has been studied with carcass traits. Significant associations were identified between g.17924A>G of FASN and carcass weight and back fat, and between the ACACA gene SNP g.2274G>A and longissimus muscle area with HPC samples. It was also found that both effects of FASN g.17924A>G and ACACA g.2274G>A polymorphisms were consistent in NLRC samples. Combined analyses of both NLRC and HPC samples also revealed the significant associations between the FASN g.17924A>G and carcass weight and back fat and between the ACACA g.2274G>A and back fat, respectively. The effect of the genotypic combination of g.17924A>G within FASN and g.2274G>A within ACACA genes showed that the combination of both GG genotypes of FASN and ACACA SNPs causes higher carcass weight and marbling score. The results of this study indicate that the two SNP markers within the FASN and ACACA genes can be utilized to select superior Hanwoo cows and calves in commercial Hanwoo farms.

• Korean Journal of Breeding Science
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• v.41 no.3
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• pp.244-251
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• 2009

This study was carried out to identify useful single gene and gene combination resistant to K1, K2, K3 and 24 bacterial blight(BB) isolates (including K3a, HB01009) breaking down Xa3 gene. Xa3, Xa4, xa5 and Xa7 genes were resistant to K1, K2, K3 of bacterial blight pathogen. Against 24 BB isolates breaking down Xa3 gene, Xa1, Xa2, xa8, Xa10, Xa11, xa13 genes were susceptible, whereas Xa4 gene was moderately resistant and xa5 and Xa21 genes were resistant. IRBB7 having Xa7 gene showed resistance responding to 24 BB isolates, whereas IRBB107 carrying Xa7 gene was susceptible to 10 BB isolates and moderately resistant to 14 BB isolates. Near-isogenic lines (NILs) of Toyonishiki and IR24, both possessing Xa7 gene, showed different resistance response against 24 BB isolates according to genetic background. Xa3+xa5, Xa4+xa5, Xa4+xa13, Xa4+Xa21, xa5+xa13, xa5+Xa21, xa13+Xa21, Xa4+xa5+xa13, Xa4+xa5+Xa21, Xa4+xa13+Xa21, xa5+xa13+Xa21, and Xa4+xa5+xa13+Xa21 were resistant to K1, K2, K3 and 24 isolates breaking down Xa3 gene. When Xa3 and xa13 genes were combined with xa5, Xa4, Xa21, resistance response was enhanced compared with single gene lines containg only Xa3 or xa13. Similarly, when Xa4 gene was combined with xa5 and Xa21, resistance response was improved by the gene combination effect.