Automated identification and characterisation of microbial populations using flow cytometry: the AIMS project
| Autor: | Linda K. Medlin, Lynne Boddy, R. R. Jonker, Laura García, Glen A. Tarran, René Groben, M. F. Wilkins, Laura Zabala |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2000 |
| Předmět: |
lcsh:SH1-691
0303 health sciences 030306 microbiology Ecology flow cytometry plankton SH1-691 Computational biology Aquatic Science Biology Oceanography lcsh:Aquaculture. Fisheries. Angling 03 medical and health sciences phytoplankton artificial neural networks rRNA probes Aquaculture. Fisheries. Angling Identification (biology) 030304 developmental biology |
| Zdroj: | Scientia Marina, Vol 64, Iss 2, Pp 225-234 (2000) ResearcherID Scientia Marina; Vol. 64 No. 2 (2000); 225-234 Scientia Marina; Vol. 64 Núm. 2 (2000); 225-234 Scientia Marina Consejo Superior de Investigaciones Científicas (CSIC) Scientia Marina; Vol 64, No 2 (2000); 225-234 |
| ISSN: | 1886-8134 0214-8358 |
| DOI: | 10.3989/scimar.2000.64n2 |
| Popis: | 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. No disponible |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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