July 2014

Prediction of substituent types and positions on skeleton of eudesmane-type sesquiterpenes using generalized regression neural network (GRNN)

Sesquiterpenes are formed from countless biogenetic pathways and are therefore a constant challenge to spectroscopists in structure elucidation. In this study, we explore the ability of generalized regression neural network (GRNN), an architecture of artificial neural networks (ANNs), to predict the substituent types on eudesmanes, one of the most representative skeletons of sesquiterpenes. Carbon-13 (13C) nuclear...

Author(s): Alawode T. T. and Alawode K. O.