| Title |
Rfam 12.0: updates to the RNA families database
|
|---|---|
| Published in |
Nucleic Acids Research, November 2014
|
| DOI | 10.1093/nar/gku1063 |
| Pubmed ID | |
| Authors | |
| Abstract |
The Rfam database (available at http://rfam.xfam.org) is a collection of non-coding RNA families represented by manually curated sequence alignments, consensus secondary structures and annotation gathered from corresponding Wikipedia, taxonomy and ontology resources. In this article, we detail updates and improvements to the Rfam data and website for the Rfam 12.0 release. We describe the upgrade of our search pipeline to use Infernal 1.1 and demonstrate its improved homology detection ability by comparison with the previous version. The new pipeline is easier for users to apply to their own data sets, and we illustrate its ability to annotate RNAs in genomic and metagenomic data sets of various sizes. Rfam has been expanded to include 260 new families, including the well-studied large subunit ribosomal RNA family, and for the first time includes information on short sequence- and structure-based RNA motifs present within families. |
Login to access the Attention Digest and the Sentiment Analysis related to this output.
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sao Tome and Principe | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 1% |
| Germany | 3 | <1% |
| Italy | 3 | <1% |
| Belgium | 2 | <1% |
| Canada | 2 | <1% |
| Czechia | 2 | <1% |
| Denmark | 2 | <1% |
| United Kingdom | 2 | <1% |
| India | 1 | <1% |
| Other | 8 | 1% |
| Unknown | 521 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 138 | 25% |
| Researcher | 133 | 24% |
| Student > Master | 65 | 12% |
| Student > Bachelor | 31 | 6% |
| Student > Doctoral Student | 29 | 5% |
| Other | 84 | 15% |
| Unknown | 73 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 208 | 38% |
| Biochemistry, Genetics and Molecular Biology | 156 | 28% |
| Computer Science | 30 | 5% |
| Environmental Science | 15 | 3% |
| Immunology and Microbiology | 12 | 2% |
| Other | 40 | 7% |
| Unknown | 92 | 17% |