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.
Mendeley readers
Attention Score in Context
| Title |
Accelerated probabilistic inference of RNA structure evolution
|
|---|---|
| Published in |
BMC Bioinformatics, March 2005
|
| DOI | 10.1186/1471-2105-6-73 |
| Pubmed ID | |
| Authors |
Ian Holmes |
| Abstract |
Pairwise stochastic context-free grammars (Pair SCFGs) are powerful tools for evolutionary analysis of RNA, including simultaneous RNA sequence alignment and secondary structure prediction, but the associated algorithms are intensive in both CPU and memory usage. The same problem is faced by other RNA alignment-and-folding algorithms based on Sankoff's 1985 algorithm. It is therefore desirable to constrain such algorithms, by pre-processing the sequences and using this first pass to limit the range of structures and/or alignments that can be considered. |
Mendeley readers
The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 3% |
| France | 1 | 1% |
| Brazil | 1 | 1% |
| Mexico | 1 | 1% |
| United States | 1 | 1% |
| Poland | 1 | 1% |
| Unknown | 60 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 21 | 31% |
| Student > Ph. D. Student | 15 | 22% |
| Student > Master | 11 | 16% |
| Professor > Associate Professor | 6 | 9% |
| Professor | 4 | 6% |
| Other | 9 | 13% |
| Unknown | 1 | 1% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 39 | 58% |
| Biochemistry, Genetics and Molecular Biology | 10 | 15% |
| Computer Science | 8 | 12% |
| Engineering | 4 | 6% |
| Immunology and Microbiology | 2 | 3% |
| Other | 3 | 4% |
| Unknown | 1 | 1% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 08 May 2016.
All research outputs
#8,475,076
of 25,287,709 outputs
Outputs from BMC Bioinformatics
#3,213
of 7,672 outputs
Outputs of similar age
#25,177
of 72,322 outputs
Outputs of similar age from BMC Bioinformatics
#3
of 4 outputs
Altmetric has tracked 25,287,709 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
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 gotten more attention than average, scoring higher than 50% 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 72,322 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one.