Linked Life Data

1990429

Source:http://linkedlifedata.com/resource/pubmed/id/1990429

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4993
pubmed:dateCreated
1991-3-6
pubmed:abstractText
Artificial networks can be used to identify hydrogen nuclear magnetic resonance (1H-NMR) spectra of complex oligosaccharides. Feed-forward neural networks with back-propagation of errors can distinguish between spectra of oligosaccharides that differ by only one glycosyl residue in twenty. The artificial neural networks use features of the strongly overlapping region of the spectra (hump region) as well as features of the resolved regions of the spectra (structural reporter groups) to recognize spectra and efficiently recognized 1H-NMR spectra even when the spectra were perturbed by minor variations in their chemical shifts. Identification of spectra by neural network-based pattern recognition techniques required less than 0.1 second. It is anticipated that artificial neural networks can be used to identify the structures of any complex carbohydrate that has been previously characterized and for which a 1H-NMR spectrum is available.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
0036-8075
pubmed:author
pubmed:issnType
Print
pubmed:day
1
pubmed:volume
251
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
542-4
pubmed:dateRevised
2007-3-19
pubmed:meshHeading
pubmed:year
1991
pubmed:articleTitle
Identification of the 1H-NMR spectra of complex oligosaccharides with artificial neural networks.
pubmed:affiliation
Complex Carbohydrate Research Center, Athens, GA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't