Abstract

Pyrolysis mass spectrometry is a data rich analysis technique now becoming widely applied in microbiology. Data analysis is a key step in the exploitation of the technique and the application of neural network analysis to pyrolysis mass spectrometric data offers new opportunities for classification, identification and inter-strain comparison of microorganisms in biotechnology and clinical microbiology. The use of a supervised neural network for the identification of members of a streptomycete species-group is described.

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