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Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
Data-driven biomedical science: implications for human disease and public health
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Data-driven biomedical science: implications for human disease and public health

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2013 한국데이터사이언스 창립기념 심포지움 발표 - 서울대학교 전주홍교수

2013 한국데이터사이언스 창립기념 심포지움 발표 - 서울대학교 전주홍교수

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  • 1. Data-driven biomedical science: implications for human disease and public health
  • 2. Better than Beatles?
  • 3. Three stages of truth - From Leslie Klevay. Query in Chapter and Verse column. Harvard Magazine. 90 (6) Whenever a new discovery is reported to the scientific world, they say first, Finally, when sufficient time has elapsed to fully evidence its importance, they say, Thereafter, when the truth of the proposition has been demonstrated beyond question, they say, "It is probably not true." "Yes, it may be true, but it is not important." "Yes, surely it is important, but it is no longer new." "Essential tension"
  • 4. 데이터 기반 연구: 무엇이 다른가? Hans Reichenbach (1891-1953) Experience and prediction (1938) “the context of discovery and the context of justification” Hypothesis-driven: rational reconstruction Data-driven: data gathering & analysis 실험연구자의 관점: 가설은 어떻게 만들어지는가?  탐사(exploration)  기술(description)  해석(explanation)
  • 5. 생물학엔 뭔가 특별한 것이 있다 Ernst Mayr (1904-2005) Causality in biology is very different from causality in classical mechanics. Compared to physicists, biologists have been little concerned about whether their findings might achieve the status of a law.
  • 6. (2008. 9. 4) 데이터를 품은 의과학 (2011. 2. 11)(2006. 3. 23)
  • 7. 미안하다 분석한다
  • 8. 관점과 개념의 변화 “Soon there will be no disease called breast cancer” Catch-all term will be replaced by “a large number of rare diseases, each of which causes malignant growth in breast tissue and require individual treatment”
  • 9. 네트워크와 역학 연구와의 만남  12,067명의 체중 증가를 소셜 네트워크를 기반으로 32년간(1971-2003년) 분석한 결과, 놀랍게도 비만이 사회적 연결망에 의해 전파된다는 것을 발견  사회적 관계성이 질환에 미치는 영향을 함께 고려함
  • 10. N Engl J Med.357, 404-407 (2007) 네트워크 의학 Multilevel networks  두 개의 질환(점)이 동일한 질환유전자를 공유하면 선으로 연결  질환유전자의 관계성을 기반으로 질환의 관계성을 예측 The human disease network PNAS (2007) 104, 8685-8690 "Disease comorbidity (co-occurrence)" Human disease network
  • 11. 척도 없는 네트워크 Normal network Disease network Disease-specific hub "Oncogene addiction" "Robust, yet fragile" Attack tolerance 대부분의 node는 소수의 link를 가짐 소수의 node만 다수의 link를 가짐 네트워크 관점 Conceptual frame: 복잡한 세상을 어떻게 표현하나? - 대상과 관계 "Targeted therapy"
  • 12. 유전자 변이: 관계의 문제 유전자 변이는 새로운 관계성을 만들어 낼 수 있다. Isocitrate dehydrogenase-1 (IDH1)의 R132H mutant는 -ketoglutarate 생산이 아니라, oncogenic metabolite인 R(-)-2-hydroxyglutarate 생산을 촉진함 Node removal vs. Edge removal "Allelic heterogeneity"
  • 13. 단백질의 은밀한 관계 From systems to structure: bridging networks and mechanism. Molecular Cell (2013) 49: 222-231 Gene-gene interaction - Epistasis - Locus heterogeneity - Synthetic lethality - Synthetic rescue Three-dimensional reconstruction of protein networks provides insight into human genetic disease. Nature Biotechnology (2012) 30: 159-164
  • 14. 성동격서 (聲東擊西) Mustard gas에 노출된 군인들이 lymphoid & myeloid cell 의 감소를 관찰함 Akylating agent
  • 15. 장계취계 (將計就計) HSP90 and the chaperoning of cancer. Nat Rev Cancer. (2005) 5:761-772
  • 16. 적재적시 (適時適材)
  • 17. 우연과 경험의 조화 Nature Reviews Drug Discovery (2004) 3: 673-683 왜 drug repositioning인가?
  • 18. 분석의 문제: 데이터는 말한다 위궤양 치료제인 cimetidine의 lung adenocarcinoma 치료 효과를 예측하고 실험으로 확인 Discovery and preclinical validation of drug Indications using compendia of public gene expression data. Science Translational Medicine (2011) 3, 96ra77 "Genomic anti-similarity" 항경련제인 topiramate의 inflammatory bowel disease 치료 효과를 예측하고 실험으로 확인 Computational repositioning of the anticonvulsant topiramate for inflammatory bowel disease. Science Translational Medicine (2011) 3, 96ra76
  • 19. Network pharmacology A B Gene or Protein "Guilt-by-association" C D Disease E Drug Network-based drug repositioning. Mol Biosyst. (In press) Cause-effect relationships in medicine: a protein network perspective. Trends Pharmacol Sci. (2010) 31, 547-555
  • 20. 의무통과점 Louis Pasteur (1822-1895) Warren Weaver (1894-1978) 록펠러 재단의 지원에 의한 신생 분자생물학(1938)의 인식론적 권위 부여 백신 개발과 보급에 의해 대중적 권위 획득 Bruno Latour (1947- ) • The extent to which current research is driven by data? • Whether this is productive? 의무통과점(obligatory passage point)
  • 21. Scientific perspectivism George E. P. Box (1919-) Essentially, all models are wrong, but some are useful.
  • 22. 융합과 창의성 • 학문분과적 사고  문제중심적 사고 • Biomedicine: convergence A B A B 중심축의 이동 (경계 넘나들기) “Repositioning”
  • 23. TRIP Database: www.trpchannel.org Ca2+ Pflugers Arch. 2010 Jul;460(2):437-50 Nucleic Acids Res. (2011) & PLoS One (2012)
  • 24. 감사합니다.

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