Publication Date:
1991-02-01
Description:
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.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Meyer, B -- Hansen, T -- Nute, D -- Albersheim, P -- Darvill, A -- York, W -- Sellers, J -- New York, N.Y. -- Science. 1991 Feb 1;251(4993):542-4.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Complex Carbohydrate Research Center, Athens, GA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/1990429" target="_blank"〉PubMed〈/a〉
Keywords:
*Artificial Intelligence
;
Carbohydrate Conformation
;
Carbohydrate Sequence
;
*Glucans
;
Hydrogen
;
Magnetic Resonance Spectroscopy/methods
;
Molecular Sequence Data
;
Oligosaccharides/*chemistry
;
Polysaccharides/*chemistry
;
*Xylans
Print ISSN:
0036-8075
Electronic ISSN:
1095-9203
Topics:
Biology
,
Chemistry and Pharmacology
,
Computer Science
,
Medicine
,
Natural Sciences in General
,
Physics
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