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

Authors

  • Richard Jonker AquaSense
  • René Groben Alfred Wegener Institute for Polar and Marine Research
  • Glen Tarran 3Centre for Coastal and Marine Sciences, Plymouth Marine Laboratory
  • Linda Medlin Alfred Wegener Institute for Polar and Marine Research
  • Malcolm Wilkins 4Cardiff School of Biosciences, University of Wales
  • Laura García University of Malaga
  • Laura Zabala University of Malaga
  • Lynne Boddy 4Cardiff School of Biosciences, University of Wales

DOI:

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

Keywords:

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

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.

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Published

2000-06-30

How to Cite

1.
Jonker R, Groben R, Tarran G, Medlin L, Wilkins M, García L, Zabala L, Boddy L. Automated identification and characterisation of microbial populations using flow cytometry: the AIMS project. scimar [Internet]. 2000Jun.30 [cited 2021Jan.20];64(2):225-34. Available from: http://scientiamarina.revistas.csic.es/index.php/scientiamarina/article/view/756

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