• Journal of Life Science
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• v.28 no.11
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• pp.1255-1261
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• 2018

Whole genome analysis have been made possible with the development of DNA sequencing technologies and discovery of many single nucleotide polymorphisms (SNPs). Large number of SNP can be analyzed with SNP chips, since SNPs of human as well as livestock genomes are available. Among the various missing nucleotide imputation programs, Minimac3 software is suggested to be highly accurate, with a simplified workflow and relatively fast. In the present study, we used Minimac3 program to perform genomic missing value substitution 1,226 animals 770K SNP chip and imputing missing SNPs with next generation sequencing data from 311 animals. The accuracy on each chromosome was about 94~96%, and individual sample accuracy was about 92~98%. After imputation of the genotypes, SNPs with R Square ($R^2$) values for three conditions were 0.4, 0.6, and 0.8 and the percentage of SNPs were 91%, 84%, and 70% respectively. The differences in the Minor Allele Frequency gave $R^2$ values corresponding to seven intervals (0, 0.025), (0.025, 0.05), (0.05, 0.1), (0.1, 0.2), (0.2, 0.3). (0.3, 0.4) and (0.4, 0.5) of 64~88%. The total analysis time was about 12 hr. In future SNP chip studies, as the size and complexity of the genomic datasets increase, we expect that genomic imputation using Minimac3 can improve the reliability of chip data for Hanwoo discrimination.

• Tuberculosis and Respiratory Diseases
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• v.62 no.5
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• pp.406-416
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• 2007

Background: Single nucleotide polymorphisms (SNPs), which consist of a substitution of a single nucleotide pair, are the most abundant form of genetic variations occurring with a frequency of approximately 1 per 1000 base pairs. SNPs by themselves do not cause disease but can predispose humans to disease, modify the extent or severity of the disease or influence the drug response and treatment efficacy. Single nucleotide polymorphisms (SNPs), particularly those within the regulatory regions of the genes often influence the expression levels and can modify the disease. Studies examining the associations between SNP and the disease outcome have provided valuable insight into the disease etiology and potential therapeutic intervention. Traditionally, the genotyping of SNPs has been carried out using polymerase chain reaction-restriction fragment length polymorphism(PCR-RFLP), which is a low throughput technique not amenable for use in large-scale SNP studies. Recently, TaqMan real-time PCR chemistry was adapted for use in allelic discrimination assays. This study validated the accuracy and utility of real-time PCR technology for SNPs genotyping Methods: The SNPs in promoter sequence (-37 and -524) of lung cancer suppressor gene, RRM1 (ribonucleotide reductase M1 subunit) with the genomic DNA samples of 89 subjects were genotyped using both real-time PCR and PCR-RFLP. Results: The discordance rates were 2.2% (2 mismatches) in -37 and 16.3% (15 mismatches) in -524. Auto-direct sequencing of all the mismatched samples(17 cases) were in accord with the genotypes read by real-time PCR. In addition, 138 genomic DNAs were genotyped using real-time PCR in a duplicate manner (two separated assays). Ninety-eight percent of the samples showed concordance between the two assays. Conclusion: Real-time PCR allelic discrimination assays are amenable to high-throughput genotyping and overcome many of the problematic features associated with PCR-RFLP.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.16
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• pp.6923-6928
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• 2015

Background: Early detection of various kinds of cancers nowadays is needed including colorectal cancer due to the highly significant effects in improving cancer treatment. The aim of this study was to evaluate the potential value of adiponectin, visfatin and resistin as early biomarkers for colorectal cancer patients. Materials and Methods: Serum levels of adiponectin, visfatin and resistin were measured by a sandwich-enzyme-linked (ELISA) assay technique in 114 serum samples comprising 34 patients with colorectal cancer (CRC), 27 with colonic polyps (CP), 24 with inflammatory bowel disease (IBD) and 29 healthy controls. The diagnostic accuracy of each serum marker was evaluated using receiver-operating characteristic (ROC) curve analysis. Results: The mean concentration of adiponectin was significantly higher in CRC and CP groups than IBD and control groups (P-value <0.05). Also the mean concentration of serum resistin was significantly elevated in the IBD and control groups compared to CRC and CP groups (P-value = 0.014). However, no significant difference was noted in patients of the CRC and CP groups. On the other hand, the mean concentration of visfatin was significantly elevated in CRC and control groups compared to CP and IBD groups (P-value = 0.03). ROC analysis curves for the studied markers revealed that between CRC and IBD groups serum level of adiponectin had a sensitivity of 76.7% and a specificity of 76% at a cut off value of 3940, +LR being 3.2 and -LR 0.31 with AUC 0.852, while serum level of adiponectin between CP and IBD had a sensitivity of 77.8% and a specificity of 75% at a cut off value of 3300, with +LR=3.11 and -LR = 0.3 with AUC 0.852. On the other hand the serum level of visfatin between CRC and CP groups had a sensitivity of 65.5% and a specificity of 66.7 at a cut off value of 2.4, +LR being 1.67 and -LR 0.52 with AUC 0.698. Also the serum level of resistin had a sensitivity of 62.5% and a specificity of 70.3% at a cut off value of 24500, with +LR=2.1 and -LR = 0.53 with AUC 0.685 between control and other groups. On the other hand by comparing control vs CP groups resistin had a sensitivity of 81.8% and a specificity of 70.8% at a cut off value of 17700, with +LR=2.8 and -LR = 0.26 with AUC 0.763 while visfatin had a sensitivity of 68.2% and a specificity of 70.8% at a cut off value of 2.7, with +LR=2.34 and -LR = 0.0.45 with AUC 0.812. Conclusions: These findings support potential roles of adiponectin, visfatin and resistin in early detection of CRC and discrimination of different groups of CRC, CP or IBD patients from normal healthy individuals.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.111-120
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• 2017

In this paper, we propose novel feature extraction algorithm for classification of seabed sediment. In previous researches, acoustic reflection coefficient has been used to classify seabed sediments, which is constant in terms of frequency. However, attenuation of seabed sediment is a function of frequency and is highly influenced by sediment types in general. Hence, we developed a feature vector by using attenuation variation with respect to frequency. The attenuation variation is obtained by using reflected signal from the second sediment layer, which is generated by broadband chirp. The proposed feature vector has advantage in number of dimensions to classify the seabed sediment over the classical scalar feature (reflection coefficient). To compare the proposed feature with the classical scalar feature, dimension of proposed feature vector is reduced by using linear discriminant analysis (LDA). Synthesised acoustic amplitudes reflected by seabed sediments are generated by using Biot model and the performance of proposed feature is evaluated by using Fisher scoring and classification accuracy computed by maximum likelihood decision (MLD). As a result, the proposed feature shows higher discrimination performance and more robustness against measurement errors than that of classical feature.

• The korean journal of orthodontics
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• v.33 no.6 s.101
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• pp.407-418
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• 2003

The purpose of this study is to analyze dentoalveolar compensation in normal occlusion samples previously classified into 9 skeletal types, and to provide clinically applicable diagnostic criteria for individual malocclusion patients. Cephalometric measurements of the 294 normal occlusion samples previously divided into 9 types were analyzed. The descriptive features of dentoalveolar variables were compared for the 9 types using analysis of variance, followed by post hoc multiple comparisons. In addition, the correlation between skeletal and dentoalveolar variables were analyzed. Discriminant analysis with a stepwise entry of variables was designed to find out several potential variables for use in skeletal typing. The dentoalveolar compensation pattern of the skeletal types varied, especially with regards to the variables that indicated the inclination of incisors and the occlusal plane. Stepwise variable selection identified four variables: AB-MP, SN-AB, PMA and ANB. Discriminant analysis assigned a classification accuracy of $87.8\%$ to the predictive model. On the basis of these results, this study could provide rudimentary information for the development of diagnostic criteria and treatment guidelines for individual skeletal types.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.599-605
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• 2017

Accurate cloud discrimination in satellite images strongly affects accuracy of remotely sensed parameter produced using it. Especially, cloud contaminated pixel over ocean is one of the major error factors such as Sea Surface Temperature (SST), ocean color, and chlorophyll-a retrievals,so accurate cloud detection is essential process and it can lead to understand ocean circulation. However, static threshold method using real-time algorithm such as Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Himawari Imager (AHI) can't fully explained reflectance variability over ocean as a function of relative positions between the sun - sea surface - satellite. In this paper, we assembled a reflectance spectral library as a function of Solar Zenith Angle (SZA) and Viewing Zenith Angle (VZA) from ocean surface reflectance with clear sky condition of Advanced Himawari Imager (AHI) identified by NOAA's cloud products and spectral library is used for applying the Dynamic Time Warping (DTW) to detect cloud pixels. We compared qualitatively between AHI cloud property and our results and it showed that AHI cloud property had general tendency toward overestimation and wrongly detected clear as unknown at high SZA. We validated by visual inspection with coincident imagery and it is generally appropriate.

• Science of Emotion and Sensibility
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• v.21 no.3
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• pp.151-164
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• 2018

The appropriate interpretation of social cues is a crucial ability for everyday life. While processing socially relevant information, beyond the low-level physical features of the stimuli to emotional information is known to influence human cognition in various stages, from early perception to later high-level cognition, such as working memory (WM). However, it remains unclear how the influence of each type of emotional information on cognitive processes changes in response to what has occurred in the processing stage. Past studies have largely adopted face stimuli to address this type of research question, but we used a unique class of socially relevant motion stimuli, called biological motion (BM), which depicts various human actions and emotions with moving dots to exhibit the effects of anger, happiness, and neutral emotion on task performance in perceptual and working memory. In this study, participants determined whether two BM stimuli, sequentially presented with a delay between them (WM task) or one immediately after the other (perceptual task), were identical. The perceptual task showed that discrimination accuracies for emotional stimuli (i.e., angry and happy) were lower than those for neutral stimuli, implying that emotional information has a negative impact on early perceptual processes. Alternatively, the results of the WM task showed that the accuracy drop as the interstimulus interval increased was actually lower in emotional BM conditions than in the neutral condition, which suggests that emotional information benefited maintenance. Moreover, anger and happiness had distinct impacts on the performance of perception and WM. Our findings have significance as we provide evidence for the interaction of type of emotion and information-processing stage.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.7
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• pp.1202-1208
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• 2020

Objective: The aim of this study was to identify a distribution pattern of meat quality grade (MQG) as a function of carcass yield index (CYI) and the gender of Hanwoo (bull, cow, and steer) to determine the optimum point between both yield and quality. We also attempted to identify how pre- and post-deboning variables affect the gender-specific beef quality of Hanwoo. Methods: A total of 31 deboning variables, consisting of 7 pre-deboning and 24 post-deboning variables from bulls (n = 139), cows (n = 69), and steers (n = 153), were obtained from the National Institute of Animal Science (NIAS) in South Korea. The database was reconstructed to be suitable for a statistical significance test between the CYI and the MQG as well as classification of meat quality. Discriminant function analysis was used for classifying MQG using the deboning parameters of Hanwoo by gender. Results: The means of CYI according to 1+, 1, 2, and 3 of MQG were 68.64±2.02, 68.85±1.94, 68.62±5.88, and 70.99±3.32, respectively. High carcass yield correlated with low-quality grade, while high-quality meat most frequently was obtained from steers. The classification ability of pre-deboning parameters was higher than that of post-deboning parameters. Moisture and the shear force were the common significant parameters in all discriminant functions having a classification accuracy of 80.6%, 71%, and 56.9% for the bull, cow, and steer, respectively. Conclusion: This study provides basic information for predicting the meat quality by gender using pre-deboning variables consistent with the actual grading index.

• Journal of Wetlands Research
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• v.7 no.2
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• pp.121-132
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• 2005

To classify the surface sedimentary facies using IKONOS image collected over Hwangdo tidal flat in Cheonsu Bay, the optical reflectance was compared for characterizing various sedimentary environments such as grain size, tidal channel pattern and area ratio of surface remnant water. The intertidal DEM (Digital Elevation Model) was generated by echo-sounder for analyzing the relationship between IKONOS image and sedimentary environments including topography. The boundary of the optical reflectance between mud-mixed facies and sand facies was distinct, and discrimination of the associated sandbar feature was also possible. The mud-mixed facies coupled with intricate tidal channels is confined to the relatively hi호 topography of Hwangdo tidal flat. The boundary between mud and mixed flat was indistinct in IKONOS optical reflectance but it would have a difference in the area ratio of surface remnant water. The dark area in the image represented the well developed sand facies having a lot of surface remnant water due to the relatively low surface topography. The overall accuracy of characterizing the surface sediment facies by maximum likelihood classification method was 86.2 %. These results demonstrate that high spatial resolution satellite imagery such as IKONOS coupled with knowledge of grain size, surface remnant water and tidal channel network can be effectively used to characterize the surface sedimentary facies (mud, mixed and sand) network of the tidal flat environments.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.111-116
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• 2013

Background: Cigarette smoking is the major risk factor for development of lung cancer. Identification of effects of tobacco on airway gene expression may provide insight into the causes. This research aimed to compare gene expression of large airway epithelium cells in normal smokers (n=13) and non-smokers (n=9) in order to find genes which discriminate the two groups and assess cigarette smoking effects on large airway epithelium cells.Materials and Methods: Genes discriminating smokers from non-smokers were identified by applying a neural network clustering method, growing self-organizing maps (GSOM), to microarray data according to class discrimination scores. An index was computed based on differentiation between each mean of gene expression in the two groups. This clustering approach provided the possibility of comparing thousands of genes simultaneously. Results: The applied approach compared the mean of 7,129 genes in smokers and non-smokers simultaneously and classified the genes of large airway epithelium cells which had differently expressed in smokers comparing with non-smokers. Seven genes were identified which had the highest different expression in smokers compared with the non-smokers group: NQO1, H19, ALDH3A1, AKR1C1, ABHD2, GPX2 and ADH7. Most (NQO1, ALDH3A1, AKR1C1, H19 and GPX2) are known to be clinically notable in lung cancer studies. Furthermore, statistical discriminate analysis showed that these genes could classify samples in smokers and non-smokers correctly with 100% accuracy. With the performed GSOM map, other nodes with high average discriminate scores included genes with alterations strongly related to the lung cancer such as AKR1C3, CYP1B1, UCHL1 and AKR1B10. Conclusions: This clustering by comparing expression of thousands of genes at the same time revealed alteration in normal smokers. Most of the identified genes were strongly relevant to lung cancer in the existing literature. The genes may be utilized to identify smokers with increased risk for lung cancer. A large sample study is now recommended to determine relations between the genes ABHD2 and ADH7 and smoking.