title: Combining spectroscopic data (MS, IR): exploratory chemometric analysis for characterising similarity/diversity of chemical structures.
abstract: 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.
authors.affiliation: ChemoAc, Pharmaceutical Institute, Vrije Universiteit Brussel, Laarbeeklaan 103, B-1090 Brussels, Belgium.
authors.forename: V
authors.initials: V
authors.lastname: Schoonjans
authors.forename: D L
authors.initials: DL
authors.lastname: Massart
mesh_terms: D013058:Mass Spectrometry / Q000379:methods*; D015394:Molecular Structure; D004364:Pharmaceutical Preparations / Q000737:chemistry* / Q000145:classification; D017550:Spectroscopy, Fourier Transform Infrared / Q000379:methods*
chemical_list: D004364:Pharmaceutical Preparations