Abstract
A general and efficient strategy for the recognition of arbitrary multiplet patterns in two-dimensional nuclear magnetic resonance spectra has been developed. It comprises cluster analysis, feature extraction, and pattern matching techniques. The corresponding C routines embedded in the graphical environment of the program AURELIA were tested successfully on two-dimensional nuclear magnetic resonance spectra of the neuropeptide head activator and the HPr proteins of Staphylococcus aureus and Streptococcus faecalis.
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