Rfam: an RNA family database

Rfam: an RNA family database

2003, Vol. 31, No. 1 | Sam Griffiths-Jones*, Alex Bateman, Mhairi Marshall, Ajay Khanna1 and Sean R. Eddy1
Rfam is a comprehensive database of multiple sequence alignments and covariance models for non-coding RNA (ncRNA) families. It aims to integrate existing curated structural RNA alignments into a common format, use covariance model software to search and maintain alignments of homologous sequences, and provide a system for automatically analyzing and annotating sequences for the presence of known structural RNAs. The database is available online and can be downloaded for local installation using the INFERNAL software suite. Rfam currently contains 25 families, annotating over 50,000 ncRNA genes in the EMBL nucleotide database. The database is designed to be user-friendly, offering features such as searching DNA sequences against covariance models, viewing annotations, and accessing multiple sequence alignments in various formats. Future developments aim to expand the database's size and scope, addressing limitations such as computational costs and the inability to model certain RNA families like microRNAs and small nucleolar RNAs.Rfam is a comprehensive database of multiple sequence alignments and covariance models for non-coding RNA (ncRNA) families. It aims to integrate existing curated structural RNA alignments into a common format, use covariance model software to search and maintain alignments of homologous sequences, and provide a system for automatically analyzing and annotating sequences for the presence of known structural RNAs. The database is available online and can be downloaded for local installation using the INFERNAL software suite. Rfam currently contains 25 families, annotating over 50,000 ncRNA genes in the EMBL nucleotide database. The database is designed to be user-friendly, offering features such as searching DNA sequences against covariance models, viewing annotations, and accessing multiple sequence alignments in various formats. Future developments aim to expand the database's size and scope, addressing limitations such as computational costs and the inability to model certain RNA families like microRNAs and small nucleolar RNAs.
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