Sulfate detection in glycoprotein-derived oligosaccharides by artificial neural network analysis of Fourier-transform infrared spectra.
Anal Biochem
; 220(1): 20-7, 1994 Jul.
Article
en En
| MEDLINE
| ID: mdl-7978246
We report the use of an artificial neural network to analyze the fingerprint region of Fourier-transform infrared (ir) spectra of oligosaccharides for the presence of sulfate groups. This assay can rapidly and nondestructively detect the presence of sulfate in as little as 1 nmol (approximately 2 micrograms) of a glycoprotein-derived monosulfated decasaccharide. The neural network was trained to recognize the presence of sulfate groups by presenting it with 45 ir spectra of sulfated and nonsulfated mono- and oligosaccharides. No prior knowledge of the characteristic ir spectral features of a sulfate group was needed as input. The training process required between 3 and 10 h, while analysis of a spectrum with the trained neural network requires only 0.1 s.
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Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Oligosacáridos
/
Ésteres del Ácido Sulfúrico
/
Glicoproteínas
/
Redes Neurales de la Computación
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Idioma:
En
Revista:
Anal Biochem
Año:
1994
Tipo del documento:
Article
Pais de publicación:
Estados Unidos