Linked Life Data

11813801

Source:http://linkedlifedata.com/resource/pubmed/id/11813801

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2002-1-29
pubmed:abstractText
Quantitative structure-toxicity (QSTR) models for the mutagenicity of a set of 95 aromatic amines were developed using four classes of calculated molecular descriptors, viz., topostructural, topochemical, geometrical and quantum chemical indices. Topochemical indices gave the best predictive model when the different classes of parameters were used separately. When hierarchical QSTRs were developed using all four classes of descriptors, there was a significant increase in explained variance by the addition of topochemical indices to the set of independent variables. The addition of geometrical and quantum chemical indices or log P to the set of descriptors resulted in very little improvement in model quality.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1062-936X
pubmed:author
pubmed:issnType
Print
pubmed:volume
12
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
481-96
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2001
pubmed:articleTitle
Prediction of mutagenicity utilizing a hierarchical QSAR approach.
pubmed:affiliation
Natural Resources Research Institute, University of Minnesota Duluth, 55811, USA. sbasak@nrri.umn.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S.