Extraction of mass spectral information by a combination of autocorrelation and principal components models

Abstract

In mass spectrometry, pattern recognition can be used for high-precision chemical structure classification provided that the mass spectra have been transformed to counteract the effect of mass spectral shifts. Autocorrelation transforms can be employed for this purpose. This transform gives results which are interpreted in terms of periodicities in the mass spectra, i.e., the loss of certain fragments from various ions.