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Application of Artificial Neural Networks for Analysis of 13C NMR Spectra of Fucoidans |
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| Authors: | Alexey G Gerbst Alexey A Grachev Nadezhda E Ustuzhanina Nikolay E Nifantiev Alexander A Vyboichtchik Alexander S Shashkov |
| Institution: | 1. Laboratory of Glycoconjugate Chemistry , N.D. Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences , Leninsky prospekt, 47, 119991, Moscow, Russia;2. Higher Chemical College, Russian Academy of Sciences , Miusskaya sq. 9, 125047, Moscow, Russia;3. Laboratory of NMR Spectroscopy , N.D. Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences , Leninsky prospekt, 47, 119991, Moscow, Russia |
| Abstract: | A new approach for structure determination of native and O-desulfated fucoidans by the analysis of their 13C NMR spectra by artificial neural networks (ANNs) is described. Two ANN models were studied: the simple three-layer feed-forward network, which employs supervised learning, and the adaptive resonance theory (ART) network with unsupervised learning. Training sets for the networks were constructed using chemical shifts of synthetic oligofucosides. The results obtained demonstrate that both models worked better in the case of desulfated fucoidans, while the ART-type networks gave better results in sulfated (native) fucoidan structure elucidation. |
| Keywords: | Fucoidans Structure elucidation NMR spectra Feed-forward neural network Adaptive resonance theory |