An identification method for enviromental bacteria is presented, based on neural network elaboration of fatty acid gas-chromatographic data and protein electrophoretic data. The reliability of identification for 99 bacterial strins was 91%, showing that the method is better than a traditional statistical approach.
Neural network integration of gas-chromatographic and electrophoretic data for the identification of environmental bacteria
GIACOMINI, MAURO;CANEVA SOUMETZ, FEDERICO;RUGGIERO, CARMELINA;
1999-01-01
Abstract
An identification method for enviromental bacteria is presented, based on neural network elaboration of fatty acid gas-chromatographic data and protein electrophoretic data. The reliability of identification for 99 bacterial strins was 91%, showing that the method is better than a traditional statistical approach.
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