RNAmmer is a computational tool for the consistent and rapid annotation of ribosomal RNA (rRNA) genes across all kingdoms of life. The tool uses hidden Markov models (HMMs) trained on data from the 5S ribosomal RNA database and the European ribosomal RNA database project. A pre-screening step allows the method to be fast with minimal loss of sensitivity, enabling the analysis of a complete bacterial genome in less than a minute. RNAmmer has been tested on all published genomes and provides accurate predictions of rRNAs. The software is available at the CBS web server. Ribosomes are molecular machines that connect nucleic acids and proteins in all living organisms. rRNAs are highly conserved in sequence and structure and are often used in comparative studies such as phylogenetic inference. However, rRNA annotations are often inconsistent or incomplete, making comparative studies challenging. RNAmmer addresses this by using HMMs to predict rRNA locations with high accuracy. The tool has been tested on a large set of genomes and has shown high accuracy in predicting rRNA locations. It also identifies novel, unannotated rRNAs in many genomes. The tool uses HMMs to predict rRNA locations, which are more effective than BLAST searches for rRNA detection. RNAmmer has been developed to use a library of HMMs for rRNA prediction. The tool is available as a web service or as a standalone package. It has been tested on all published genomes and gives accurate predictions of rRNAs. The program also produces results that are comparable between genomes. RNAmmer has been used to predict the three major rRNA species: 16S, 23S, and 5S in prokaryotes, and 18S, 5.8S, and 28S in eukaryotes. The tool has been tested on a variety of genomes and has shown high accuracy in predicting rRNA locations. It has also identified novel, unannotated rRNAs in many genomes. The tool is available at the CBS web server and is used for genome analysis. The tool has been compared to other rRNA prediction methods, including RFAM, and has shown high accuracy in predicting rRNA locations. The tool is also used for computational speed testing and has been shown to be faster than other methods. The tool is available as a traditional HTML-based prediction server and through a SOAP-based web service. It is also available for download through the same site.RNAmmer is a computational tool for the consistent and rapid annotation of ribosomal RNA (rRNA) genes across all kingdoms of life. The tool uses hidden Markov models (HMMs) trained on data from the 5S ribosomal RNA database and the European ribosomal RNA database project. A pre-screening step allows the method to be fast with minimal loss of sensitivity, enabling the analysis of a complete bacterial genome in less than a minute. RNAmmer has been tested on all published genomes and provides accurate predictions of rRNAs. The software is available at the CBS web server. Ribosomes are molecular machines that connect nucleic acids and proteins in all living organisms. rRNAs are highly conserved in sequence and structure and are often used in comparative studies such as phylogenetic inference. However, rRNA annotations are often inconsistent or incomplete, making comparative studies challenging. RNAmmer addresses this by using HMMs to predict rRNA locations with high accuracy. The tool has been tested on a large set of genomes and has shown high accuracy in predicting rRNA locations. It also identifies novel, unannotated rRNAs in many genomes. The tool uses HMMs to predict rRNA locations, which are more effective than BLAST searches for rRNA detection. RNAmmer has been developed to use a library of HMMs for rRNA prediction. The tool is available as a web service or as a standalone package. It has been tested on all published genomes and gives accurate predictions of rRNAs. The program also produces results that are comparable between genomes. RNAmmer has been used to predict the three major rRNA species: 16S, 23S, and 5S in prokaryotes, and 18S, 5.8S, and 28S in eukaryotes. The tool has been tested on a variety of genomes and has shown high accuracy in predicting rRNA locations. It has also identified novel, unannotated rRNAs in many genomes. The tool is available at the CBS web server and is used for genome analysis. The tool has been compared to other rRNA prediction methods, including RFAM, and has shown high accuracy in predicting rRNA locations. The tool is also used for computational speed testing and has been shown to be faster than other methods. The tool is available as a traditional HTML-based prediction server and through a SOAP-based web service. It is also available for download through the same site.