Correction

Novel opportunities for computational biology and sociology in drug discovery (vol 27, pg 531, 2009)

Journal

TRENDS IN BIOTECHNOLOGY
Volume 28, Issue 4, Pages 161-170

Publisher

ELSEVIER SCIENCE LONDON
DOI: 10.1016/j.tibtech.2010.01.004

Keywords

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Funding

  1. NATIONAL CANCER INSTITUTE [U54CA121852] Funding Source: NIH RePORTER
  2. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [R01GM061372] Funding Source: NIH RePORTER
  3. NATIONAL INSTITUTE OF MENTAL HEALTH [P50MH094267] Funding Source: NIH RePORTER
  4. NATIONAL LIBRARY OF MEDICINE [R01LM010132] Funding Source: NIH RePORTER
  5. NCI NIH HHS [U54 CA121852-01A1, U54 CA121852] Funding Source: Medline
  6. NCI NIH HHS [U54 CA121852, U54 CA121852-01A1] Funding Source: Medline
  7. NIGMS NIH HHS [R01 GM061372-09, R01 GM061372-08, R01 GM061372, R01 GM061372-07, GM61372] Funding Source: Medline
  8. NIGMS NIH HHS [R01 GM061372, GM61372] Funding Source: Medline
  9. NIMH NIH HHS [P50 MH094267] Funding Source: Medline
  10. NLM NIH HHS [R01 LM010132] Funding Source: Medline

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Current drug discovery is impossible without sophisticated modeling and computation. In this review we outline previous advances in computational biology and, by tracing the steps involved in pharmaceutical development, explore a range of novel, high-value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy industry links for scientific and human benefit. Attention to these opportunities could promise punctuated advance and will complement the well-established computational work on which drug discovery currently relies.

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