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 |
Partition function and base pairing probabilities of RNA heterodimers
|
|---|---|
| Published in |
Algorithms for Molecular Biology, March 2006
|
| DOI | 10.1186/1748-7188-1-3 |
| Pubmed ID | |
| Authors |
Stephan H Bernhart, Hakim Tafer, Ulrike Mückstein, Christoph Flamm, Peter F Stadler, Ivo L Hofacker |
| Abstract |
RNA has been recognized as a key player in cellular regulation in recent years. In many cases, non-coding RNAs exert their function by binding to other nucleic acids, as in the case of microRNAs and snoRNAs. The specificity of these interactions derives from the stability of inter-molecular base pairing. The accurate computational treatment of RNA-RNA binding therefore lies at the heart of target prediction algorithms. |
Mendeley readers
The data shown below were compiled from readership statistics for 218 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 3% |
| Austria | 3 | 1% |
| United Kingdom | 2 | <1% |
| France | 1 | <1% |
| New Zealand | 1 | <1% |
| Germany | 1 | <1% |
| Denmark | 1 | <1% |
| Argentina | 1 | <1% |
| Unknown | 202 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 59 | 27% |
| Researcher | 49 | 22% |
| Student > Master | 21 | 10% |
| Student > Bachelor | 18 | 8% |
| Professor | 14 | 6% |
| Other | 26 | 12% |
| Unknown | 31 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 87 | 40% |
| Biochemistry, Genetics and Molecular Biology | 44 | 20% |
| Computer Science | 22 | 10% |
| Medicine and Dentistry | 6 | 3% |
| Chemistry | 4 | 2% |
| Other | 21 | 10% |
| Unknown | 34 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 06 January 2021.
All research outputs
#3,272,356
of 22,789,076 outputs
Outputs from Algorithms for Molecular Biology
#22
of 264 outputs
Outputs of similar age
#7,248
of 67,002 outputs
Outputs of similar age from Algorithms for Molecular Biology
#1
of 1 outputs
Altmetric has tracked 22,789,076 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 264 research outputs from this source. They receive a mean Attention Score of 3.2. This one has done particularly well, scoring higher than 91% 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 67,002 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% 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