| Title |
Condor-COPASI: high-throughput computing for biochemical networks
|
|---|---|
| Published in |
BMC Systems Biology, July 2012
|
| DOI | 10.1186/1752-0509-6-91 |
| Pubmed ID | |
| Authors |
Edward Kent, Stefan Hoops, Pedro Mendes |
| Abstract |
Mathematical modelling has become a standard technique to improve our understanding of complex biological systems. As models become larger and more complex, simulations and analyses require increasing amounts of computational power. Clusters of computers in a high-throughput computing environment can help to provide the resources required for computationally expensive model analysis. However, exploiting such a system can be difficult for users without the necessary expertise. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 25% |
| United Kingdom | 1 | 25% |
| Colombia | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Scientists | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 1% |
| Malaysia | 1 | 1% |
| Indonesia | 1 | 1% |
| Latvia | 1 | 1% |
| United Kingdom | 1 | 1% |
| Singapore | 1 | 1% |
| Denmark | 1 | 1% |
| Russia | 1 | 1% |
| United States | 1 | 1% |
| Other | 1 | 1% |
| Unknown | 72 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 23 | 28% |
| Student > Ph. D. Student | 19 | 23% |
| Student > Master | 9 | 11% |
| Student > Bachelor | 8 | 10% |
| Professor | 4 | 5% |
| Other | 9 | 11% |
| Unknown | 10 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 31 | 38% |
| Computer Science | 16 | 20% |
| Biochemistry, Genetics and Molecular Biology | 7 | 9% |
| Engineering | 6 | 7% |
| Medicine and Dentistry | 5 | 6% |
| Other | 6 | 7% |
| Unknown | 11 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 06 February 2023.
All research outputs
#2,367,585
of 23,715,461 outputs
Outputs from BMC Systems Biology
#56
of 1,135 outputs
Outputs of similar age
#15,208
of 166,088 outputs
Outputs of similar age from BMC Systems Biology
#3
of 35 outputs
Altmetric has tracked 23,715,461 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,135 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done particularly well, scoring higher than 95% 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 166,088 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.