19569715

Source:http://linkedlifedata.com/resource/pubmed/id/19569715

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Predicate	Object
rdf:type	pubmed:Citation
lifeskim:mentions	umls-concept:C0023175, umls-concept:C0025664, umls-concept:C0150098, umls-concept:C0525063, umls-concept:C0887819, umls-concept:C1707455, umls-concept:C2698650
pubmed:issue	7
pubmed:dateCreated	2009-7-27
pubmed:abstractText	2D and 3D QSAR techniques are widely used in lead optimization-like processes. A compilation of 40 diverse data sets is described. It is proposed that these can be used as a common benchmark sample for comparisons of QSAR methodologies, primarily in terms of predictive ability. Use of this benchmark set will be useful for both assessment of new methods and for optimization of existing methods.
pubmed:language	eng
pubmed:journal	http://linkedlifedata.com/resource/pubmed/journal/101230060
pubmed:citationSubset	IM
pubmed:status	MEDLINE
pubmed:month	Jul
pubmed:issn	1549-9596
pubmed:author	pubmed-author:McKinnonRoss ARA, pubmed-author:MittalRuchi RRR, pubmed-author:SorichMichael JMJ
pubmed:issnType	Print
pubmed:volume	49
pubmed:owner	NLM
pubmed:authorsComplete	Y
pubmed:pagination	1810-20
pubmed:meshHeading	pubmed-meshheading:19569715-Databases, Factual, pubmed-meshheading:19569715-Drug Discovery, pubmed-meshheading:19569715-Molecular Structure, pubmed-meshheading:19569715-Quantitative Structure-Activity Relationship
pubmed:year	2009
pubmed:articleTitle	Comparison data sets for benchmarking QSAR methodologies in lead optimization.
pubmed:affiliation	Sansom Institute, School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, South Australia 5000, Australia.
pubmed:publicationType	Journal Article, Comparative Study