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Attention Score in Context
| Title |
URDME: a modular framework for stochastic simulation of reaction-transport processes in complex geometries
|
|---|---|
| Published in |
BMC Systems Biology, June 2012
|
| DOI | 10.1186/1752-0509-6-76 |
| Pubmed ID | |
| Authors |
Brian Drawert, Stefan Engblom, Andreas Hellander |
| Abstract |
Experiments in silico using stochastic reaction-diffusion models have emerged as an important tool in molecular systems biology. Designing computational software for such applications poses several challenges. Firstly, realistic lattice-based modeling for biological applications requires a consistent way of handling complex geometries, including curved inner- and outer boundaries. Secondly, spatiotemporal stochastic simulations are computationally expensive due to the fast time scales of individual reaction- and diffusion events when compared to the biological phenomena of actual interest. We therefore argue that simulation software needs to be both computationally efficient, employing sophisticated algorithms, yet in the same time flexible in order to meet present and future needs of increasingly complex biological modeling. |
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 % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 4% |
| Switzerland | 2 | 3% |
| Norway | 1 | 1% |
| Japan | 1 | 1% |
| Unknown | 73 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 26 | 33% |
| Student > Ph. D. Student | 20 | 25% |
| Student > Master | 9 | 11% |
| Professor | 6 | 8% |
| Student > Bachelor | 2 | 3% |
| Other | 5 | 6% |
| Unknown | 12 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 15 | 19% |
| Agricultural and Biological Sciences | 14 | 18% |
| Mathematics | 8 | 10% |
| Biochemistry, Genetics and Molecular Biology | 7 | 9% |
| Physics and Astronomy | 4 | 5% |
| Other | 20 | 25% |
| Unknown | 12 | 15% |
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 2022.
All research outputs
#7,048,335
of 23,063,209 outputs
Outputs from BMC Systems Biology
#270
of 1,144 outputs
Outputs of similar age
#49,709
of 165,042 outputs
Outputs of similar age from BMC Systems Biology
#9
of 38 outputs
Altmetric has tracked 23,063,209 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 1,144 research outputs from this source. They receive a mean Attention Score of 3.6. 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 165,042 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 38 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.