Linked Life Data

19691315

Source:http://linkedlifedata.com/resource/pubmed/id/19691315

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
36
pubmed:dateCreated
2009-9-9
pubmed:abstractText
A pattern-based recognition approach for the rapid determination of the identity, concentration, and enantiomeric excess of chiral vicinal diols, specifically threo diols, has been developed. A diverse enantioselective sensor array was generated using three chiral boronic acid receptors and three pH indicators. The optical response produced by the sensor array was analyzed by two pattern-recognition algorithms: principal component analysis and artificial neural networks. Principal component analysis demonstrated good chemoselective and enantioselective separation of the analytes, and an artificial neural network was used to accurately determine the concentrations and enantiomeric excesses of five unknown samples with an average absolute error of +/-0.08 mM in concentration and 3.6% in enantiomeric excess. The speed of the analysis was enhanced by using a 96-well plate format, portending applications in high-throughput screening for asymmetric-catalyst discovery. X-ray crystallography and (11)B NMR spectroscopy was utilized to study the enantioselective nature of the boronic acid host 2.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
1520-5126
pubmed:author
pubmed:issnType
Electronic
pubmed:day
16
pubmed:volume
131
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
13125-31
pubmed:dateRevised
2011-5-27
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Pattern-based recognition for the rapid determination of identity, concentration, and enantiomeric excess of subtly different threo diols.
pubmed:affiliation
Department of Chemistry and Biochemistry, The University of Texas at Austin, Austin, Texas 78712, USA.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Evaluation Studies, Research Support, N.I.H., Extramural