Simulation of the 13C Nuclear Magnetic Resonance Spectra of Ribonucleosides Using Multiple Linear Regression Analysis and Neural Networks
Deborah L. Clouser, Peter C. Jurs · Journal of Chemical Information and Computer Sciences · 1996
Regression equations have been developed to predict the 13 C NMR spectra of 17 ribonucleosides through the use of atomic environmental descriptors. These descriptors were calculated directly from the structure of the compounds. Fifteen compounds are used as a training set for linear regression analysis, and two compounds are used as an external prediction set. Due to the diverse nature of the atoms within the data set, the chemical shifts were divided into subsets. The results for each subset are reported. Computational neural networks are also used to predict the chemical shifts of the atoms in the subsets.