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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Accelerating calculations of RNA secondary structure partition functions using GPUs
|
|---|---|
| Published in |
Algorithms for Molecular Biology, November 2013
|
| DOI | 10.1186/1748-7188-8-29 |
| Pubmed ID | |
| Authors |
Harry A Stern, David H Mathews |
| Abstract |
RNA performs many diverse functions in the cell in addition to its role as a messenger of genetic information. These functions depend on its ability to fold to a unique three-dimensional structure determined by the sequence. The conformation of RNA is in part determined by its secondary structure, or the particular set of contacts between pairs of complementary bases. Prediction of the secondary structure of RNA from its sequence is therefore of great interest, but can be computationally expensive. In this work we accelerate computations of base-pair probababilities using parallel graphics processing units (GPUs). |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 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 % |
|---|---|---|
| Germany | 1 | 6% |
| Canada | 1 | 6% |
| Unknown | 15 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 24% |
| Student > Ph. D. Student | 3 | 18% |
| Professor > Associate Professor | 3 | 18% |
| Student > Master | 2 | 12% |
| Student > Doctoral Student | 2 | 12% |
| Other | 1 | 6% |
| Unknown | 2 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 35% |
| Computer Science | 4 | 24% |
| Biochemistry, Genetics and Molecular Biology | 3 | 18% |
| Medicine and Dentistry | 2 | 12% |
| Unknown | 2 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 November 2017.
All research outputs
#6,932,484
of 22,731,677 outputs
Outputs from Algorithms for Molecular Biology
#63
of 264 outputs
Outputs of similar age
#64,476
of 213,637 outputs
Outputs of similar age from Algorithms for Molecular Biology
#2
of 5 outputs
Altmetric has tracked 22,731,677 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 264 research outputs from this source. They receive a mean Attention Score of 3.2. This one has gotten more attention than average, scoring higher than 74% 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 213,637 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.