The characterization of natural microbial assemblages in community profiling projects introduces the major scientific challenges of understanding and predicting the function and response to environmental changes of microbes of an ecosystem. Here, we present a system for the automatic analysis of ARISA data sets. ARISA is a method for analyzing the composition of microbial communities, which performs faster and at a much lower cost than other community profiling techniques. ARISA relies on the analysis of intergenic regions called internal transcribed spacer (ITS), which are located between the 16S and 23S rRNA genes. The database ADAPTdb was created to store and maintain ITS regions along with information about their source organisms. The data stored in

ADAPTdb is retrieved from< different data resources, such as the Entrez sequence databases. The program ADAPT was developed to taxonomically characterize ARISA data sets using ADAPTdb. The additional organism information for each ITS region in the ADAPTdb database is used by ADAPT for pathogenic and autotrophic/heterotrophic comparisons of organisms among different ARISA samples. The program is publicly available through a user-friendly web interface, which allows onsite analysis of ARISA data sets and computation of the output. The interactive web interface facilitates navigation through the output and export functionality for subsequent analysis.