Sulfate Detection in Glycoprotein-Derived Oligosaccharides by Artificial Neural Network Analysis Fourier-Transform Infrared Spectra
✍ Scribed by D.A. Powell; V. Turula; J.A. Dehaseth; H. Vanhalbeek; B. Meyer
- Book ID
- 102965126
- Publisher
- Elsevier Science
- Year
- 1994
- Tongue
- English
- Weight
- 670 KB
- Volume
- 220
- Category
- Article
- ISSN
- 0003-2697
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✦ Synopsis
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 ((\approx 2 \mu \mathrm{g})) 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 monoand 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 \mathrm{~h}), while analysis of a spectrum with the trained neural network requires only 0.1 s. cc 1994 Academic Press, Inc.