title: Interpretation of gascromatographic data via artificial neural networks for the classification of marine bacteria.
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.
authors.affiliation: Dep. of Comm., Comp., and System Science, University of Genova, Italy.
authors.forename: C
authors.initials: C
authors.lastname: Ruggiero
authors.forename: M
authors.initials: M
authors.lastname: Giacomini
authors.forename: F
authors.initials: F
authors.lastname: Calegari
authors.forename: R
authors.initials: R
authors.lastname: Berti
authors.forename: S
authors.initials: S
authors.lastname: Bertone
authors.forename: L
authors.initials: L
authors.lastname: Casareto
mesh_terms: D000465:Algorithms; D001709:Biotechnology; D002849:Chromatography, Gas; D005069:Evaluation Studies as Topic; D005227:Fatty Acids / Q000032:analysis; D006090:Gram-Negative Bacteria / Q000737:chemistry / Q000145:classification* / Q000302:isolation & purification; D008386:Marine Biology; D016571:Neural Networks, Computer; D014871:Water Microbiology
chemical_list: D005227:Fatty Acids