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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Flexible composition and execution of high performance, high fidelity multiscale biomedical simulations
|
|---|---|
| Published in |
Interface Focus, April 2013
|
| DOI | 10.1098/rsfs.2012.0087 |
| Pubmed ID | |
| Authors |
D. Groen, J. Borgdorff, C. Bona-Casas, J. Hetherington, R. W. Nash, S. J. Zasada, I. Saverchenko, M. Mamonski, K. Kurowski, M. O. Bernabeu, A. G. Hoekstra, P. V. Coveney |
| Abstract |
Multiscale simulations are essential in the biomedical domain to accurately model human physiology. We present a modular approach for designing, constructing and executing multiscale simulations on a wide range of resources, from laptops to petascale supercomputers, including combinations of these. Our work features two multiscale applications, in-stent restenosis and cerebrovascular bloodflow, which combine multiple existing single-scale applications to create a multiscale simulation. These applications can be efficiently coupled, deployed and executed on computers up to the largest (peta) scale, incurring a coupling overhead of 1-10% of the total execution time. |
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 % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 7% |
| Unknown | 42 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 27% |
| Student > Ph. D. Student | 8 | 18% |
| Professor > Associate Professor | 4 | 9% |
| Student > Master | 4 | 9% |
| Other | 3 | 7% |
| Other | 8 | 18% |
| Unknown | 6 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 13 | 29% |
| Computer Science | 12 | 27% |
| Physics and Astronomy | 4 | 9% |
| Agricultural and Biological Sciences | 2 | 4% |
| Chemistry | 2 | 4% |
| Other | 3 | 7% |
| Unknown | 9 | 20% |
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 25 February 2013.
All research outputs
#15,265,264
of 22,699,621 outputs
Outputs from Interface Focus
#417
of 579 outputs
Outputs of similar age
#124,673
of 199,506 outputs
Outputs of similar age from Interface Focus
#7
of 7 outputs
Altmetric has tracked 22,699,621 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 579 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.8. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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 199,506 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one.