Combining spectroscopic data (MS, IR): exploratory chemometric analysis for characterising similarity/diversity of chemical structures

Combined infrared-mass spectra (IR-MS) have been used to examine a small data set of synthetic substances in order to elucidate whether a combination of spectral descriptors yield better classification and similarity predictions than their corresponding individual spectral descriptors. To eliminate differences in variation. a logarithmic transformation or log double-centering pretreatment was necessary. Principal component analysis (PCA) was applied to observe clusters of similar compounds. Hierarchical upgma-cluster analysis was also used for data classification. (C) 2001 Elsevier Science B.V. All rights reserved.