Scientia Marina, Vol 64, No 2 (2000)

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


https://doi.org/10.3989/scimar.2000.64n2225

Richard Jonker
AquaSense, Netherlands

René Groben
Alfred Wegener Institute for Polar and Marine Research, Germany

Glen Tarran
3Centre for Coastal and Marine Sciences, Plymouth Marine Laboratory, United Kingdom

Linda Medlin
Alfred Wegener Institute for Polar and Marine Research, Germany

Malcolm Wilkins
4Cardiff School of Biosciences, University of Wales, United Kingdom

Laura García
University of Malaga, Spain

Laura Zabala
University of Malaga, Spain

Lynne Boddy
4Cardiff School of Biosciences, University of Wales, United Kingdom

Abstract


The AIMS (Automatic Identification and characterisation of Microbial populationS) 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 approaches and molecular probes to the identification of cell populations, and deriving and verifying algorithms for assessing the chemical, optical and morphometric characteristics of these populations. The products of AIMS will be calibrated data, protocols, algorithms and software designed to turn flow cytometric observations into a data matrix of the abundance and cellular characteristics of identifiable populations. This paper describes the general approach of the AIMS project, with details on the application of artificial neural nets and rRNA oligonucleotide probes.

Keywords


plankton; phytoplankton; flow cytometry; artificial neural networks; rRNA probes

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