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Mendeley readers
Attention Score in Context
| Title |
Efficient procedures for the numerical simulation of mid-size RNA kinetics
|
|---|---|
| Published in |
Algorithms for Molecular Biology, September 2012
|
| DOI | 10.1186/1748-7188-7-24 |
| Pubmed ID | |
| Authors |
Iddo Aviram, Ilia Veltman, Alexander Churkin, Danny Barash |
| Abstract |
Methods for simulating the kinetic folding of RNAs by numerically solving the chemical master equation have been developed since the late 90's, notably the programs Kinfold and Treekin with Barriers that are available in the Vienna RNA package. Our goal is to formulate extensions to the algorithms used, starting from the Gillespie algorithm, that will allow numerical simulations of mid-size (~ 60-150 nt) RNA kinetics in some practical cases where numerous distributions of folding times are desired. These extensions can contribute to analyses and predictions of RNA folding in biologically significant problems. |
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 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 8% |
| United States | 1 | 8% |
| Unknown | 10 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 50% |
| Student > Bachelor | 2 | 17% |
| Professor | 1 | 8% |
| Student > Master | 1 | 8% |
| Researcher | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 1 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 42% |
| Agricultural and Biological Sciences | 5 | 42% |
| Engineering | 1 | 8% |
| Unknown | 1 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 15 September 2012.
All research outputs
#18,314,922
of 22,678,224 outputs
Outputs from Algorithms for Molecular Biology
#197
of 264 outputs
Outputs of similar age
#128,924
of 169,032 outputs
Outputs of similar age from Algorithms for Molecular Biology
#3
of 6 outputs
Altmetric has tracked 22,678,224 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 264 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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We're also able to compare this research output to 6 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.