Major gene interactions effect identification on the quality of Hanwoo by radial graph

Lee, Jea-Young; Bae, Jae-Young; Lee, Jin-Mok; Oh, Do Hoon; Lee, Seong-Won

doi:10.7465/jkdi.2013.24.1.151

Cited by 3 publications

(1 citation statement)

References 8 publications

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“…These improvements include making statistical summaries more visual and providing more information at the same time (Symanzik and Carr, 2008), and they were further practiced in many researches (Cho, 2012;Han et al, 2012;Wong et al, 2012;Lee et al, 2013;Ha and Noh, 2013;Cho, 2014).…”

Section: Related Workmentioning

confidence: 99%

Visualization and interpretation of cancer data using linked micromap plots

Park¹,

Ahn²

2014

Journal of the Korean Data and Information Science Society

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The causes of cancer are diverse, complex, and only partially understood. Many factors including health behaviors, socioeconomic environments and geographical locations can directly damage genes or combine with existing genetic faults within cells to cause cancerous mutations. Collecting the cancer data and reporting the statistics, therefore, are important to help identify health trends and establish normal health changes in geographical areas. In this article, we analyzed cancer data and demonstrated how spatial patterns of the age-standardized rate and health indicators can be examined visually and simultaneously using linked micromap plots. As a result of data analysis, the age-standardized rate has positive correlativity with thyroid and breast cancer, but the rate has negative correlativity with smoking and drinking. In addition, the regions with high age-standardized rate are located in southwest and the areas of high population density while the standardized mortality ratio is higher in southwest and northeast where there are lots of rural areas.

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Section: Related Workmentioning

confidence: 99%

Visualization and interpretation of cancer data using linked micromap plots

Park¹,

Ahn²

2014

Journal of the Korean Data and Information Science Society

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A survey study of farmers' recognition on reality of Hanwoo raising and improving quality : Focused on Gyeongsangbuk-Do

Kim¹,

Oh²,

Jung³

et al. 2014

Journal of the Korean Data and Information Science Society

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Major gene identification for SREBPs and FABP4 gene which are associated with fatty acid composition of Korean cattle

Lee¹,

Jang²,

Oh³

2015

Journal of the Korean Data and Information Science Society

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678Jae-Young Lee · Ji-Eun Jang · Dong-Yep Oh 2013b). 본 논문의 분석에 사용된 경제형질은 올레인산 (oleic acid; C18:1), 불포화지방산 (monounsaturated fatty acid; MUFA), 근내지방도 (marbling score; MS)로, 올레인산과 불포화지방산은 쇠고기의 풍미 를 좋게 해주는 것으로 알려져 있으며 (Yoshimura와 Namikawa, 1983), 쇠고기의 육질에 영향을 주는 근내지방도 또한 다즙성, 풍미와 밀접한 관련이 있다 (Lee 등, 1994(Lee 등, , 2013a Monson 등, 2005;Oh, 2014) Step 0. 전체 SNP그룹을 정한다.Major gene identification for SREBPs and FABP4 gene in Korean cattle 679Step 1. 전체 L개의 SNP그룹에서 랜덤으로 k개의 SNP를 A라는 그룹으로 선택, 나머지는 SN Pi로 둔다.Step 2. SN Pi 중 하나와 A그룹의 SNP를 1:1로 k번 교체하여 각각 스코어를 낸다.Step 3.Step 2에서 계산된 스코어 중 가장 큰 값을 A * 로 정한다.Step 4.Step 3에서 나온 A * 그룹의 스코어와 초기A그룹의 스코어를 비교하여Step 5.Step 4에서 그룹이 결정되었다면, SN Pi+1을 이용하여 Step 2∼Step 4를 반복한다.Step 6.Step 2∼Step 5 (q (반복수)=2 or 3)를 반복하며, 최종으로 나온 A * 스코어가 이전의 A스코어 보다 작을 경우 멈추게 된다. A>T, g.2988 A>G, g.3690 G>A, g.3710 G>C, g.3977-325 T>C, g.4221 A>G를 활용하였다 (Oh, 2014. Table 3.2는 k-평균 군집분석을 통해 이분화 된 데이터의 평균, 표준편 차를 나타낸 표이다. Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer. AbstractDisease of human and economic traits of livestocks are affected a lot by gene combination effect rather than a single gene effect. In this study, we used SNPHarvester method that supplement existing method in order to investigate the interaction of these genes. The used genes are SREBPs (g.3270+10274 C>T, g.13544 T>C) and FABP4 (g.2634+1018 A>T, g.2988 A>G, g.3690 G>A, g.3710 G>C, g.3977-325 T>C, g.4221 A>G) that are closely related to the fatty acid composition affecting the meatiness of Korean cattle. The economic traits which are used are oleic acid (C18:1), monounsaturated fatty acid (MUFA), marbling score (MS). First, we have utilized the SNPHarvester method in order to find excellent gene combination, and then used the multifactor dimensionality reduction method in order to identify excellent genotype in gene combination.

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Major gene interactions effect identification on the quality of Hanwoo by radial graph

Cited by 3 publications

References 8 publications

Visualization and interpretation of cancer data using linked micromap plots

Visualization and interpretation of cancer data using linked micromap plots

A survey study of farmers' recognition on reality of Hanwoo raising and improving quality : Focused on Gyeongsangbuk-Do

Major gene identification for SREBPs and FABP4 gene which are associated with fatty acid composition of Korean cattle

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