Automated identification and characterisation of microbial populations using flow cytometry: the AIMS project

The AIMS (Automatic Identification and characterisation of Microbial popula tionS) project is developing and integrating flow cytometric technology for the identification of microbial cell populations and the determination of their cellular characteristics. This involves applying neural network appro aches and molecular probes to the identification of cell populations, and d eriving and verifying algorithms for assessing the chemical, optical and mo rphometric characteristics of these populations. The products of AIMS will be calibrated data, protocols, algorithms and software designed to turn flo w cytometric observations into a data matrix of the abundance and cellular characteristics of identifiable populations. This paper describes the gener al approach of the AIMS project, with details on the application of artific ial neural nets and rRNA oligonucleotide probes.