Whereas dedicated computational approaches have been developed for the search of C/D sRNAs and snoRNAs, as yet no dedicated computational approach has been developed for the search of archaeal H/ACA sRNAs. Here we describe a computational approach allowing a fast and selective identification of H/ACA sRNAs in archaeal genomes. It is easy to use, even for biologists having no special expertise in computational biology. This approach is a stepwise knowledge-based approach, combining the search for common structural features of H/ACA motifs and the search for their putative target sequences. The first step is based on the ERPIN software. It depends on the establishment of a secondary structure-based "profile." We explain how this profile is built and how to use ERPIN to optimize the search for H/ACA motifs. Several examples of applications are given to illustrate how powerful the method is, its limits, and how the results can be evaluated. Then, the possible target rRNA sequences corresponding to the identified H/ACA motifs are searched by use of a descriptor-based method (RNAMOT). The principles and the practical aspects of this method are also explained, and several examples are given here as well to help users in the interpretation of the results.