Hierarchical clustering of carbon-13 nulear magnetic resonance spectra

The problems of preprocessing of ¹³C-n.m.r. spectra for hierarchical clustering are discussed. Encoding of the spectra in nonequidistant intervals is proposed. To establish the optimal intervals, a Simplex method with variable-sized movements is used. The optimized parameter is the amount of information contained in the first two coordinates of the transforms, obtained by the application of principal component analysis to the ¹³C-n.m.r. spectra. The spectra encoded in optimized intervals are used for automated structure elucidation, based on a hierarchical organization of a collection of more than 2000 assigned¹³C-n.m.r. spectra. The hierarchical trees needed for the library search and prediction of some structural features were generated by a 3-distances clustering method. The retrieval and predictive abilities of the system are discussed.