• Asian-Australasian Journal of Animal Sciences
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• v.27 no.12
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• pp.1691-1694
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• 2014

Copy number variation (CNV) or single nucleotide phlyorphism (SNP) is useful genetic resource to aid in understanding complex phenotypes or deseases susceptibility. Although thousands of CNVs and SNPs are currently avaliable in the public databases, they are somewhat difficult to use for analyses without visualization tools. We developed a web-based tool called the VCS (visualization of CNV or SNP) to visualize the CNV or SNP detected. The VCS tool can assist to easily interpret a biological meaning from the numerical value of CNV and SNP. The VCS provides six visualization tools: i) the enrichment of genome contents in CNV; ii) the physical distribution of CNV or SNP on chromosomes; iii) the distribution of log2 ratio of CNVs with criteria of interested; iv) the number of CNV or SNP per binning unit; v) the distribution of homozygosity of SNP genotype; and vi) cytomap of genes within CNV or SNP region.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.215-224
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• 2010

Most chronic diseases are complex diseases which are caused by interactions of several genes. Studies on finding SNPs and gene-gene interactions involved in the development of complex diseases can contribute to prevention and treatment of the diseases. Previous studies mostly concentrate on finding only the set of SNPs involved. In this study we suggest a way to see how these SNPs interact using boolean expressions. The proposed method consists of two stages. In the first stage we find the set of SNPs involved in the development of diseases using mutual information based on entropy. In the second stage we find the highest accuracy boolean expression that consists of the SNP set obtained in the first stage. We experimented with clinical data to demonstrate the effectiveness of the proposed method. We also compared the differences between our method and the previous results on the SNP associations studies.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.4
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• pp.334-340
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• 2001

Two different types of molecular markers, simple sequence repeat (SSR) and single nucleotide polymorphism (SNP), were used to measure genetic diversity among five Korean, eight Thai, and three wild soybeans. For SSR analysis, a total of 20 markers were surveyed to detect polymorphisms. For SNP analysis, four primers were designed from consensus sequence regions on disease resistance protein homolog genes, and used to amplify the genomic region. The PCR products were sequenced. A number of polymorphic SSR and SNP bands were scored on all genotypes and their genetic similarity was measured. Clustering analysis was performed independently on both types of markers. Clustering based on SSR markers separated the genotypes into three main groups originated from Korea, Thailand, and wild soybeans. On the other hand, two main groups were classified using SNP analysis. It seemed that SSR was more informative than SNP in this study. This may be due to the fact that SNP was surveyed on the smaller genomic region than SSR. Grouping based on the combined data of both markers revealed similar results to that of SNP rather than that of SSR. This might be due to the fact that more loci from SNP were considered to measure genetic relatedness than those from the SSR.

• BMB Reports
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• v.40 no.1
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• pp.95-99
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• 2007

Bovine coding region single nucleotide polymorphisms located proximal to quantitative trait loci were identified to facilitate bovine QTL fine mapping research. A total of 692,763 bovine SNPs was extracted from 39,432 UniGene clusters, and 53,446 candidate SNPs were found to be a depth >3. In order to validate the in silico SNPs experimentally, 186 animals representing 14 breeds and 100 mixed breeds were analyzed. Genotyping of 40 randomly selected candidate SNPs revealed that 43% of these SNPs ranged in frequency from 0.009 to 0.498. To identify non-synonymous SNPs and to correct for possible frameshift errors in the ESTs at the predicted SNP positions, we designed a program that determines coding regions by protein-sequence referencing, and identified 17,735 nsSNPs. The SNPs and bovine quantitative traits loci informations were integrated into a bovine SNP data: BcSNPdb (http://snugenome.snu.ac.kr/BtcSNP/). Currently there are 43 different kinds of quantitative traits available. Thus, these SNPs would serve as valuable resources for exploiting genomic variation that influence economically and agriculturally important traits in cows.

• Genomics & Informatics
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• v.8 no.3
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• pp.138-141
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• 2010

Together with single nucleotide polymorphism (SNP), copy number variations (CNV) are recognized to be the major component of human genetic diversity and used as a genetic marker in many disease association studies. Affymetrix Genome-wide SNP 5.0 is one of the commonly used SNP array platforms for SNP-GWAS as well as CNV analysis. However, there has been no report that validated the accuracy and reproducibility of CNVs identified by Affymetrix SNP array 5.0. In this study, we compared the characteristics of CNVs from the same set of genomic DNAs detected by three different array platforms; Affymetrix SNP array 5.0, Agilent 2X244K CNV array and NimbleGen 2.1M CNV array. In our analysis, Affymetrix SNP array 5.0 seems to detect CNVs in a reliable manner, which can be applied for association studies. However, for the purpose of defining CNVs in detail, Affymetrix Genome-wide SNP 5.0 might be relatively less ideal than NimbleGen 2.1M CNV array and Agilent 2X244K CNV array, which outperform Affymetrix array for defining the small-sized single copy variants. This result will help researchers to select a suitable array platform for CNV analysis.

• Animal Bioscience
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• v.37 no.3
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• pp.428-436
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• 2024

Objective: This study compared five distinct sets of biological pathways and associated genes related to semen volume (VOL), number of sperm (NS), and sperm motility (MOT) in the Thai multibreed dairy population. Methods: The phenotypic data included 13,533 VOL records, 12,773 NS records, and 12,660 MOT records from 131 bulls. The genotypic data consisted of 76,519 imputed and actual single nucleotide polymorphisms (SNPs) from 72 animals. The SNP additive genetic variances for VOL, NS, and MOT were estimated for SNP windows of one SNP (SW1), ten SNP (SW10), 30 SNP (SW30), 50 SNP (SW50), and 100 SNP (SW100) using a single-step genomic best linear unbiased prediction approach. The fixed effects in the model were contemporary group, ejaculate order, bull age, ambient temperature, and heterosis. The random effects accounted for animal additive genetic effects, permanent environment effects, and residual. The SNPs explaining at least 0.001% of the additive genetic variance in SW1, 0.01% in SW10, 0.03% in SW30, 0.05% in SW50, and 0.1% in SW100 were selected for gene identification through the NCBI database. The pathway analysis utilized genes associated with the identified SNP windows. Results: Comparison of overlapping and non-overlapping SNP windows revealed notable differences among the identified pathways and genes associated with the studied traits. Overlapping windows consistently yielded a larger number of shared biological pathways and genes than non-overlapping windows. In particular, overlapping SW30 and SW50 identified the largest number of shared pathways and genes in the Thai multibreed dairy population. Conclusion: This study yielded valuable insights into the genetic architecture of VOL, NS, and MOT. It also highlighted the importance of assessing overlapping and non-overlapping SNP windows of various sizes for their effectiveness to identify shared pathways and genes influencing multiple traits.

• Journal of Animal Science and Technology
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• v.52 no.2
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• pp.91-96
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• 2010

The purpose of the study was to develop an optimum SNP marker set to be utilized for domestic pork traceability. The study tested 51 SNP markers analyzed for origin of farm to be determined from genotypes of offspring and parents in pigs. With the simulation data through random mating population (PI), half sib mating population ($PI_{half-sib}$) and full sib mating population ($PI_{sibs}$), probability of identical genotypes were analyzed as $5.63{\times}10^{-33}$, $4.35{\times}10^{-15}$ and $1.32{\times}10^{-15}$, respectively. The 51 SNP markers also had 100% accuracy for parental determination. These results suggest that if the pig breeding stock is genotyped with the 51 SNP markers, the genotype information of individual offspring can be checked for farm origins by tracing parental sow and sire. Therefore, these SNP markers will be useful to trace the pork from production to consumption in pigs.

• Journal of Animal Science and Technology
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• v.50 no.6
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• pp.775-782
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• 2008

This study was aimed to find SNPs related with marbling score in Hanwoo(Korean cattle) using BcSNPdb. This study was searched QTL region related with marbling score and extracted 3,605 SNPs by applying BcSNPdb. Among these SNPs, 347 nonsynonymous SNP were selected and 160 SNPs were verified by PCR and finally proven with application to experimental data of the national progeny test. BTS_003888, BTS_012665 and BTS_009454 candidate SNPs were revealed significantly associated with marbling score(P<0.05), and BTS_025951 candidate SNPs was significantly associated with backfat thickness(P<0.05). From the result, SNPs from BTS_003888, BTS_009454, BTS_052584 and BTS_025951 were considered to be useful for the advancement in selective improved model in marbling score and backfat thickness of Hanwoo.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.435-438
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• 2006

Single Nucleotide Polymorphism(SNP)는 인간 유전자 서열의 0.1%에 해당하는 부분으로 이는 각 개인의 체질 및 각종 유전질환과 밀접한 관련이 있다고 알려져 있으며 이 SNP 정보를 이용 각종 질환의 유전적 원인규명에 대한 많은 생물학적 연구가 진행되고 있다. 그러나 아직 SNP를 이용한 효율적인 분석방법에 대한 전산학적 연구는 많지 않다. 본 논문에서는 대표적인 패턴인식기 중 하나인 Support Vector Machine(SVM)을 이용 한국인의 대표적인 유전질환으로 알려진 위암에 대한 예측율을 실험하였다. 실험 데이터는 간 및 소화기 질환 유전체 센터에서 얻어진 위 질환 환자를 대상으로 하였으며 실험 결과 예측율은 67.3%로 이는 Case Based Reasoning(CBR)방법의 55% 보다 더 좋은 예측 결과를 보였다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.238-240
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• 2003

게놈 프로젝트에 의해 인간 유전자 영기서열이 밝혀지면서 개개인의 유전자에 나타나는 SNP(Single Nucleotide Polymorphism)을 분석하여 질병의 진단과 예후, 치료와 예방이 미래에 가능하게 되었다. 본 논문은 그러한 SNP 분석을 위한 자동 분석 시스템의 영상 처리 과정으로서, 기존의 육안을 통해 분석하였던 TDGS 영상을 본 시스템의 자동적인 영상 처리 과정을 통해 SNP 분석을 위한 디지털 패턴을 추출한다. SNP 분석을 위해 사용되는 샘플은 대략 수백개가 되는데, 실험이라는 특성상 영상에 나타나는 불규칙한 요소들이 많고. 영상의 상태가 좋지 않은 경우 명암도가 낮은 반점들의 구분이 힘들게 된다. 본 논문에서는 TDGS 영상의 지역적 특성을 가장 잘 반영하기 위한 동적 이진화의 새로운 척도를 제안하였고, 영상에서 잡영과 배경을 제거한 후 남겨진 관심영역을 반점으로 판별하여 이를 디지털 패턴으로 추출한 결과를 보여 준다.