You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Evaluation of several lightweight stochastic context-free grammars for RNA secondary structure prediction
|
|---|---|
| Published in |
BMC Bioinformatics, June 2004
|
| DOI | 10.1186/1471-2105-5-71 |
| Pubmed ID | |
| Authors |
Robin D Dowell, Sean R Eddy |
| Abstract |
We describe a general approach to several RNA sequence analysis problems using probabilistic models that flexibly describe the secondary structure and primary sequence consensus of an RNA sequence family. We call these models 'covariance models'. A covariance model of tRNA sequences is an extremely sensitive and discriminative tool for searching for additional tRNAs and tRNA-related sequences in sequence databases. A model can be built automatically from an existing sequence alignment. We also describe an algorithm for learning a model and hence a consensus secondary structure from initially unaligned example sequences and no prior structural information. Models trained on unaligned tRNA examples correctly predict tRNA secondary structure and produce high-quality multiple alignments. The approach may be applied to any family of small RNA sequences. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 50% |
| New Zealand | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 125 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 3% |
| France | 2 | 2% |
| Italy | 2 | 2% |
| Hungary | 1 | <1% |
| Brazil | 1 | <1% |
| United Kingdom | 1 | <1% |
| Germany | 1 | <1% |
| Mexico | 1 | <1% |
| New Zealand | 1 | <1% |
| Other | 2 | 2% |
| Unknown | 109 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 42 | 34% |
| Researcher | 27 | 22% |
| Student > Master | 12 | 10% |
| Professor > Associate Professor | 9 | 7% |
| Professor | 7 | 6% |
| Other | 16 | 13% |
| Unknown | 12 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 54 | 43% |
| Computer Science | 25 | 20% |
| Biochemistry, Genetics and Molecular Biology | 21 | 17% |
| Mathematics | 3 | 2% |
| Engineering | 3 | 2% |
| Other | 5 | 4% |
| Unknown | 14 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 28. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 November 2023.
All research outputs
#1,368,926
of 25,287,709 outputs
Outputs from BMC Bioinformatics
#166
of 7,672 outputs
Outputs of similar age
#1,563
of 63,282 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 1 outputs
Altmetric has tracked 25,287,709 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,672 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 97% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 63,282 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them