AIMS (Automated Identification System For Microbial Populations) is an EU MAST III project that will develop, test and apply analytical procedures to identify and characterise phytoplankton using in situ hybridisation and flow cytometry coupled to artificial neural networks (ANN). Ribosomal RNA sequences, especially the 18S rRNA, will be used to develop specific oligonucleotide probes for detecting different groups, genera and species of algae for confirmation of the species identification made with ANNs. 18S rRNA sequences retrieved from GenBank were added to unpublished sequences from nano- and picoplankton taxa to build up an algal sequence database. Sequence data were analysed using the ARB program to find unique regions for designing specific probes. Oligonucleotides complementary to these sites were labelled with fluorochromes or with enzymes and hybridised to different algae or the PCR products of their 18S rRNA gene for subsequent analysis using chemiluminescent detection or fluorescent detection with microscopy or flow cytometry. Specific probes are currently available for algae at a higher group level (i.e., green versus non-green algae), at the class level (i.e., Pelagophyceae, Prymnesiophyceae), for two clades of Chrysochromulina species, for the genus Phaeocystis and for the species Alexandrium tamarense, Chrysochromulina polylepis, and several species of Pseudo-nitzschia. Probes that have been developed and are now being tested are among others specific for dinoflagellates and pennate diatoms, the genus Pyramimonas, six clades within the Cryptophyta and the species Emiliania huxleyi, Gymnodinium mikimotoi, Heterocapsa triquetra, Phaeocystis globosa, Prorocentrum lima, P. minimum, P. micans and Skeletonema costatum. Probes will be developed for the genera Gymnodinium (in part) and Chaetoceros. A broad range of algal taxa can be identified and counted rapidly with ANNs, and their identification reconfirmed with rRNA probes.