Title :
Neural network integration of gas-chromatographic and electrophoretic data for the identification of environmental bacteria
Author :
Bertone, S. ; Giacomini, M. ; Soumetz, F. Caneva ; Ruggiero, C. ; Calegari, L.
Author_Institution :
RILAB s.r.l., Genoa, Italy
Abstract :
An identification method for environmental 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 strains was 91%, showing that the method is better than a traditional statistical approach
Keywords :
biochemistry; biological techniques; biology computing; chromatography; electrophoresis; microorganisms; proteins; self-organising feature maps; unsupervised learning; electrophoretic data; environmental bacteria identification; fatty acid gas-chromatographic data; gas-chromatographic data; marine bacterial strains; neural network integration; protein electrophoretic data; reliability; Artificial neural networks; Biochemical analysis; Biochemistry; Capacitive sensors; Medical diagnostic imaging; Microorganisms; Neural networks; Protein engineering; Stacking; Systematics;
Conference_Titel :
[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-5674-8
DOI :
10.1109/IEMBS.1999.804087
