Linked Life Data

20349528

Source:http://linkedlifedata.com/resource/pubmed/id/20349528

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2010-3-26
pubmed:abstractText
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.
pubmed:grant
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
1879-3096
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
28
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
161-70
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Novel opportunities for computational biology and sociology in drug discovery.
pubmed:affiliation
Department of Biomedical Informatics, Center for Computational Biology and Bioinformatics, Columbia University, New York, NY 10032, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S., Review, Corrected and Republished Article, Research Support, N.I.H., Extramural