Linked Life Data

16889226

Source:http://linkedlifedata.com/resource/pubmed/id/16889226

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2006-8-7
pubmed:abstractText
Quantitative structure-activity relationship (QSAR) models play a key role in lead optimization, where the focus is on increased efficiency and lower attrition. When experimental data becomes rate limiting, a suitable model can bridge the experimental resource gap and direct investigation of a lead series toward productive lines. Technically, QSAR models can be readily generated and published to a wide community via the World Wide Web. We therefore focus this review on issues affecting model quality rather than on cataloguing models that are available. We also review the area of inverse QSAR, in which a model can be harnessed to semi-automated methods to provide an efficient way to explore vast areas of chemical space.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
1367-6733
pubmed:author
pubmed:issnType
Print
pubmed:volume
9
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
419-24
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Exploiting QSAR methods in lead optimization.
pubmed:affiliation
Novartis Institutes for BioMedical Research, CH-4002 Basel, Switzerland. nathan.brown@novartis.com
pubmed:publicationType
Journal Article, Review