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The Korean HapMap Project Website
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기타
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  • The Korean HapMap Project Website
  • The Korean HapMap Project Website
저자명
Kim. Young-Uk,Kim. Seung-Ho,Jin. Hoon,Park. Young-Kyu,Ji. Mi-Hyun,Kim. Young-Joo
간행물명
Genomics & informatics
권/호정보
2008년|6권 2호|pp.91-94 (4 pages)
발행정보
한국유전체학회
파일정보
정기간행물|ENG|
PDF텍스트
주제분야
기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
서지반출

기타언어초록

Single nucleotide polymorphisms (SNPs) are the most abundant form of human genetic variation and are a resource for mapping complex genetic traits. A genome is covered by millions of these markers, and researchers are able to compare which SNPs predominate in people who have a certain disease. The International HapMap Project, launched in October, 2002, motivated us to start the Korean HapMap Project in order to support Korean HapMap infrastructure development and to accelerate the finding of genes that affect health, disease, and individual responses to medications and environmental factors. A Korean SNP and haplotype database system was developed through the Korean HapMap Project to provide Korean researchers with useful data-mining information about disease-associated biomarkers for studies on complex diseases, such as diabetes, cancer, and stroke. Also, we have developed a series of software programs for association studies as well as the comparison and analysis of Korean HapMap data with other populations, such as European, Chinese, Japanese, and African populations. The developed software includes HapMapSNPAnalyzer, SNPflank, HWE Test, FESD, D2GSNP, SNP@Domain, KMSD, KFOD, KFRG, and SNP@WEB. We developed a disease-related SNP retrieval system, in which OMIM, GeneCards, and MeSH information were integrated and analyzed for medical research scientists. The kHapMap Browser system that we developed and integrated provides haplotype retrieval and comparative study tools of human ethnicities for comprehensive disease association studies (http://www.khapmap.org). It is expected that researchers may be able to retrieve useful information from the kHapMap Browser to find useful biomarkers and genes in complex disease association studies and use these biomarkers and genes to study and develop new drugs for personalized medicine.