Automatic identification of terpenoid skeletons by feed-forward neural networks.
Fiche publication
Date publication
octobre 2006
Auteurs
Membres identifiés du Cancéropôle Est :
Dr NUZILLARD Jean-Marc
Tous les auteurs :
Emerenciano VP, Alvarenga SA, Scotti MT, Ferreira MJ, Stefani R, Nuzillard JM
Lien Pubmed
Résumé
Feed-forward neural networks (FFNNs) were used to predict the skeletal type of molecules belonging to six classes of terpenoids. A database that contains the 13C NMR spectra of about 5000 compounds was used to train the FFNNs. An efficient representation of the spectra was designed and the constitution of the best FFNN input vector format resorted from an heuristic approach. The latter was derived from general considerations on terpenoid structures.
Référence
Anal Chim Acta. 2006 Oct 10;579(2):217-26