FLOW CYTOMETRY DATA PROCESSING FOR ANTIMICROBIAL AGENT SENSIBILITY PREDICTION

A method for predicting the sensibility phenotype of a test microorganism to an antimicrobial agent amongst susceptible, intermediate and resistant phenotypes, comprising a learning stage and a prediction stage. The learning stage comprises selecting a wide set of different strains having different...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	RAMJEET, Mahendrasingh, MAHE, Pierre, CHAPEL, Margaux, KANEKO, Gael
Format:	Patent
Sprache:	eng ; fre ; ger
Schlagworte:	BEER BIOCHEMISTRY CHEMISTRY COMPOSITIONS OR TEST PAPERS THEREFOR CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL ORENZYMOLOGICAL PROCESSES ENZYMOLOGY INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEICACIDS OR MICROORGANISMS METALLURGY MICROBIOLOGY MUTATION OR GENETIC ENGINEERING PHYSICS PROCESSES OF PREPARING SUCH COMPOSITIONS SPIRITS VINEGAR WINE
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Beschreibung
Zusammenfassung:	A method for predicting the sensibility phenotype of a test microorganism to an antimicrobial agent amongst susceptible, intermediate and resistant phenotypes, comprising a learning stage and a prediction stage. The learning stage comprises selecting a wide set of different strains having different known sensibility phenotypes determined according EUCAST or CLSI method, acquiring FCM (flow cytometry) distributions for each of said strain aliquoted in liquid samples with fluorescent markers and different concentrations of the antibiotic, and performing a learning machine computing on mono or multidimensional spaces involving feature vectors derived from the FCM acquisition to derive a prediction model of the sensibility phenotype to the antibiotic.