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Updated: May 24, 2026

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
Published on: February 25, 2021
Interpretation of gascromatographic data via artificial neural networks for the classification of marine bacteria
C Ruggiero1, M Giacomini, F Calegari
1Dep. of Comm., Comp., and System Science, University of Genova, Via All'Opera Pia 11a, 16145, Genova, Italy.
Abstract:
We propose a new method for classification of marine bacteria. This method uses gaschromatograms, which contain information of fatty acid percentage contents of the fresh isolate. For the interpretation of these gaschromatograms we use a surpervisioned artificial neural network. We present a preliminary study on this matter, whose first results show good convergence and classification features.
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