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제목 2015년 11월 25일 수요일 생물정보학세미나
작성자 관리자 작성일 2015-11-20

서울대학교 생물정보연구소와 생물정보학 협동과정 공동 주최로 특별 세미나를 아래와 같이 열고자 하오니, 많은 참여 바랍니다.

　

일시: 2015년 11월 25일 수요일 오전 11시

연사: 한복기 (질병관리본부 국립보건연구원 유전체센터)

장소: 서울대학교 25동 411호

　

Title: Preparation of Data Analyzing for the Future Medicine

Abstract

A central challenge for medicine in this century is implementing personalized medicine to optimize a medical effectiveness for individual based on the level of genetic data. In addition to genetic data, various information such as phenotype and omics data needs to be analyzed together to predict and find cause of disease more efficiently. A rapid reduction of genome sequencing cost has led to the utilization of individual whole genome analysis, thus, expectations are larger than ever. Large scale of genome data and other types of data, including even mobile health data will be analyzed in biomedical research. In these days, the rate of data generation becomes faster and the type of data becomes more diverse. Thus, researchers will face to manage more amounts of different types of data.

As related technologies such as next-generation DNA chip analysis technology, high-speed whole genome sequencing technology, various genome analysis platform, and bioinformatics-based processing algorithm have been rapidly advanced, personalized medicine becomes more realizable in terms of the technology as well as the cost.

In 2011, National Research Council preferred the term “precision medicine” to “personalized medicine.” There was concern that the word “personalized” could be misinterpreted to imply that treatments and preventions are being developed uniquely for each individual; in precision medicine, the focus is on identifying which approaches will be effective for which patients based on genetic, environmental, and lifestyle factors (Source: Genetics Home Reference, NLM).

Precision Medicine Initiative (PMI) in U.S receives attention and expects to cure cancer and diabetes and maintain healthier life by collecting large scale cohort and analyzing omics data, personal health data from mobile device, and environmental related data.

In this lecture, PMI and related current trends in Korea will be introduced to prepare the near future and realize the importance of data analyzing technology.


Education

부산대학교 학사, 1981

부산대학교 석사, 1983

독일　Bonn　대학교 박사, 1993


Experience

질병관리본부 국립보건연구원 유전체센터장　(2009 ~　현재)

카타르　Biobank　국제자문위원　(2011 ~　현재)

고려대학교 의과대학 외래교수　(2006 ~　현재)

한국유전체학회 부회장　(2009 ~ 2014)

국제후성유전체컨소시움(IHEC)　공동위원장　(2011 ~ 2012)


주요연구업적

1. Genetically determined height and coronary artery diesease, Nelson CP, Hamby SE, Saleheen D et al.;CARDioGRAM+C4D consortium, N Engl J Med. 2015 Apr 23;372(17):1608-18.

2. Genetic studies of body mass index yield new insights for obesity biology, Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, Powell C et al, Nature. 2015 Feb 12;518(7538):197-206.

3. New genetic loci link adipose and insulin biology to body fat distribution.

4. Genome-wide association meta-analysis identifies novel variants associated with fasting plasma glucose in East Asians, Hwang JY¹, Han BG, Cho YS, Kim BJ et al, Diabetes. 2015 Jan;64(1):291-8.

5. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility, Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) Consortium; Type 2 Diabetes Genetic Exploration by Nex-generation sequencing in muylti-Ethnic Samples (T2D-GENES) Consortium et al, Nat Genet. 2014 Mar;46(3):234-44.

6. Recapitulation of previous genome-wide association studies with two distinct pathophysiological entities of gastric cancer in the Korean population, Hwang JY¹, Kim DH, Ji YI, Jin Go M, Heo L, Jin Kim Y, Sung Sihn T, Hyung Noh J, Kim S, Lee YS, Kim SY, Kim YW, Won Ryu K, Choi IJ, Lee J, Kim BJ, Han BG, Park J, Lee JY, J Hum Genet. 2013 Apr;58(4):233-5.

7. Meta-analysis identifies multiple loci associated with kidney function-related traits in east Asian populations, Okada Y¹, Sim X, Go MJ, Kim YJ, Lee JY, Han BG, et al, Nat Genet. 2012 Jul 15;44(8):904-9.

8. Meta-analysis identifies common variants associated with body mass index in east Asians, Wen W¹, Cho YS, Long J, Han BG et al, Nat Genet. 2012 Feb 19;44(3):307-11.

9. Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians, Cho YS¹, Chen CH, Han BG, Seielsted M et al, Nat Genet. 2011 Dec 11;44(1):67-72.　

　

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