✦ LIBER ✦

Simulation of 13C nuclear magnetic resonance spectra of tetrahydropyrans using regression analysis and neural networks

✍ Scribed by Deborah L. Clouser; Peter C. Jurs

Publisher: Elsevier Science
Year: 1994
Tongue: English
Weight: 956 KB
Volume: 295
Category: Article
ISSN: 0003-2670
DOI: 10.1016/0003-2670(94)80227-0

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✦ Synopsis

The 13C NMR spectra of tetrahydropyrans are simulated directly from their molecular structures. A set of 29 tetrahydropyrans is used as a training set to generate regression equations and to train neural networks, and three additional compounds are used as a cross-validation set. The results of simulations done by regression analysis are found to be extremely sensitive to molecular geometries. To account for this, two different methods of descriptor manipulation, an averaging method and a Boltzmann-weighted averaging method, are introduced, and the models generated from the descriptor sets are compared. The results for the Boltzmann-weighted averaging method are found to be better than those based on descriptors derived from only the lowest energy conformation.

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