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


Contact
rgroben [ at ] awi-bremerhaven.de

Abstract

The AIMS (Automatic Identification and characterisation of Microbial populationS) project is developing and integrating flowcytometric 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 derivingand verifying algorithms for assessing the chemical, optical and morphometric characteristics of these populations. The productsof AIMS will be calibrated data, protocols, algorithms and software designed to turn flow cytometric observations into a datamatrix of the abundance and cellular characteristics of identifiable populations. This paper describes the general approach of theAIMS project, with details on the application of artificial neural nets and rRNA oligonucleotide probes.



Item Type
Article
Authors
Divisions
Programs
Peer revision
Scopus/ISI peer-reviewed
Publication Status
Published
Eprint ID
3504
Cite as
Jonker, R. , Groben, R. , Tarran, G. , Medlin, L. , Wilkins, M. , Garcia, L. , Zabala, L. and Boddy, L. (2000): Automated identification and characterisation of microbial populations using flow cytometry: the AIMS Project , Scientia marina, 64 , pp. 225-234 .


Share

Research Platforms
N/A

Campaigns


Actions
Edit Item Edit Item