| Title |
Rfam: updates to the RNA families database
|
|---|---|
| Published in |
Nucleic Acids Research, October 2008
|
| DOI | 10.1093/nar/gkn766 |
| Pubmed ID | |
| Authors |
Paul P. Gardner, Jennifer Daub, John G. Tate, Eric P. Nawrocki, Diana L. Kolbe, Stinus Lindgreen, Adam C. Wilkinson, Robert D. Finn, Sam Griffiths-Jones, Sean R. Eddy, Alex Bateman |
| Abstract |
Rfam is a collection of RNA sequence families, represented by multiple sequence alignments and covariance models (CMs). The primary aim of Rfam is to annotate new members of known RNA families on nucleotide sequences, particularly complete genomes, using sensitive BLAST filters in combination with CMs. A minority of families with a very broad taxonomic range (e.g. tRNA and rRNA) provide the majority of the sequence annotations, whilst the majority of Rfam families (e.g. snoRNAs and miRNAs) have a limited taxonomic range and provide a limited number of annotations. Recent improvements to the website, methodologies and data used by Rfam are discussed. Rfam is freely available on the Web at http://rfam.sanger.ac.uk/and http://rfam.janelia.org/. |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 2% |
| United Kingdom | 5 | 1% |
| Sweden | 3 | <1% |
| France | 3 | <1% |
| Brazil | 2 | <1% |
| New Zealand | 2 | <1% |
| Norway | 2 | <1% |
| Chile | 2 | <1% |
| Italy | 2 | <1% |
| Other | 11 | 3% |
| Unknown | 348 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 91 | 24% |
| Student > Ph. D. Student | 89 | 23% |
| Student > Master | 44 | 11% |
| Student > Bachelor | 26 | 7% |
| Student > Doctoral Student | 18 | 5% |
| Other | 64 | 17% |
| Unknown | 54 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 201 | 52% |
| Biochemistry, Genetics and Molecular Biology | 61 | 16% |
| Computer Science | 23 | 6% |
| Medicine and Dentistry | 7 | 2% |
| Environmental Science | 6 | 2% |
| Other | 24 | 6% |
| Unknown | 64 | 17% |