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Mendeley readers
Attention Score in Context
Title |
Random generation of RNA secondary structures according to native distributions
|
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Published in |
Algorithms for Molecular Biology, October 2011
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DOI | 10.1186/1748-7188-6-24 |
Pubmed ID | |
Authors |
Markus E Nebel, Anika Scheid, Frank Weinberg |
Abstract |
Random biological sequences are a topic of great interest in genome analysis since, according to a powerful paradigm, they represent the background noise from which the actual biological information must differentiate. Accordingly, the generation of random sequences has been investigated for a long time. Similarly, random object of a more complicated structure like RNA molecules or proteins are of interest. |
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 % |
---|---|---|
Unknown | 2 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 6% |
Unknown | 16 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 5 | 29% |
Researcher | 3 | 18% |
Professor | 3 | 18% |
Student > Bachelor | 2 | 12% |
Professor > Associate Professor | 2 | 12% |
Other | 1 | 6% |
Unknown | 1 | 6% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 6 | 35% |
Computer Science | 5 | 29% |
Biochemistry, Genetics and Molecular Biology | 2 | 12% |
Mathematics | 1 | 6% |
Chemical Engineering | 1 | 6% |
Other | 2 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 29 October 2011.
All research outputs
#3,224,913
of 22,655,397 outputs
Outputs from Algorithms for Molecular Biology
#21
of 264 outputs
Outputs of similar age
#17,855
of 135,954 outputs
Outputs of similar age from Algorithms for Molecular Biology
#2
of 4 outputs
Altmetric has tracked 22,655,397 research outputs across all sources so far. Compared to these this one has done well and is in the 85th 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 92% 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 135,954 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 86% of its contemporaries.
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. This one has scored higher than 2 of them.