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

일시: 2018년 4월 19일 목요일 오후 5시

연사: 이인석(연세대학교)

장소: 서울대학교 25동 411호

TITLE: Network-argumented Analysis of Disease Genomics Data

ABSTRACT: Recent genomic revolution opened new avenues to understanding human disease. However, it also revealed complex nature of human disease. For example, currently more than several hundred genes are believed to be associated to human cancer. Genome-wide association study (GWAS) suggests hundreds of disease-related genes, but together explaining only 10-20% of total disease inheritance at most. Because of this overwhelming complexity of disease-causing pathway, modern disease genetics needs to be more systematic and predictive. However, the network organization of disease systems also provide big opportunity to investigate the genetic organization of complex diseases through the molecular networks. Our research group has developed co-functional gene networks for many organisms including human (HumanNet) and various network-guided methods to identify novel disease genes and modules. In this talk, I will present our recent work in network-based augmenting and interpreting cancer somatic mutation data (MUFFINN), GWAS data for complex diseases (GWAB), and gene set enrichment analysis for disease transcriptome data (NGSEA).

EDUCATION AND TRAINING

B.S., Biology, Hanyang University, Seoul, Korea (03/1986 – 02/1993)

M.S., Biology, Western Illinois University, Macomb, IL (09/1993 – 05/1996)

Ph.D., Microbiology, University of Texas at Austin, TX (09/1996 – 12/2002)

01/2003 – 02/2008 Postdoc Fellow/Research Associate, Center for Systems and Synthetic Biology, University of Texas, Austin, TX, USA

03/2008 – 02/2012 Assistant professor, Department of Biotechnology, Yonsei University,

03/2012 – 02/2017 Associate professor, Department of Biotechnology, Yonsei University,

03/2017 – Present Professor, Department of Biotechnology, Yonsei University,

SELECTED PUBLICATION

Han H, Cho JW, Lee S, Yun A, Kim H, Bae D, Yang S, Kim CY, Lee M, Kim E, Lee S, Kang B, Jeong D, Kim Y, Jeon HN, Jung H, Nam S, Chung M, Kim JH, Lee I, TRRUST v2: An expanded reference database of human and mouse transcriptional regulatory interactions Nucleic Acids Research 2018 Jan 4; 46(D1):D380–D386

Shim JE, Bang C, Yang S, Lee T, Hwang S, Kim CY, Singh-Blom M, Marcotte E, Lee I, GWAB: a web server for the network-based boosting of human genome-wide association data, Nucleic Acids Research 2017 Apr 26; 45 (W1):W154-W161

Yang S, Kim CY, Hwang S, Kim E, Kim H, Shim H, Lee I*, COEXPEDIA: exploring biomedical hypotheses via co-expressions associated with medical subject headings (MeSH), Nucleic Acids Research 2017 Jan 4;

Shim H, Kim JH, Kim CY, Hwang S, Kim H, Yang S, Lee JE*, Lee I*, Function-driven discovery of disease genes in zebrafish using an integrated genomics big data resource, Nucleic Acids Research 2016 Nov 16;44(20):9611-9623

Shim JE, Lee I. Weighted mutual information analysis substantially improves domain-based functional network models. Bioinformatics 2016 Sep 15; 32:2824-30

Cho A, Shim JE, Kim E, Supek F. Lehner B*. Lee I*. MUFFINN: cancer gene discovery via network analysis of somatic mutation data. Genome Biology 2016 June 23; 17:129

Jo J, Hwang S, Kim HJ, Hong S, Lee JE, Lee SG, Baek A, Han H, Lee JI, Lee I*, Lee DR*. An integrated systems biology approach identifies positive cofactor 4 as a factor that increases reprogramming efficiency. Nucleic Acids Research 2016 Feb 18; 44(3):1203-15.

Kim E, Hwang S, Kim H, Shim H, Kang B, Yang S, Shim JH, Shin SY, Marcotte EM, Lee I. MouseNet v2: A database of gene networks for studying the laboratory mouse and eight other model vertebrates, Nucleic Acids Research 2016 Jan 4;44(D1):D848-54

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