Linked Life Data

20593816

Source:http://linkedlifedata.com/resource/pubmed/id/20593816

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
7
pubmed:dateCreated
2010-7-29
pubmed:abstractText
Principal component analysis (PCA) of a large data matrix (153 solvents x 396 solutes) for Ostwald solubility coefficients (log L) resulted in a two-component model covering 98.6% of the variability. Analysis of the principal components exposed the structural characteristics of solutes and solvents that codify interactions which determine the behavior of a chemical in the surrounding media. The pattern revealed by PCA analysis distinguishes solutes according to the molecular size, functional groups, and electrostatic interactions, such as polarity and hydrogen-bonding donor and acceptor properties.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
1549-960X
pubmed:author
pubmed:issnType
Electronic
pubmed:day
26
pubmed:volume
50
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1275-83
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
A general treatment of solubility 4. Description and analysis of a PCA model for ostwald solubility coefficients.
pubmed:affiliation
Institute of Chemistry, University of Tartu, 14A Ravila, Tartu 50411, Estonia.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't