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X Demographics
Mendeley readers
Attention Score in Context
| Title |
RuleBender: integrated modeling, simulation and visualization for rule-based intracellular biochemistry
|
|---|---|
| Published in |
BMC Bioinformatics, May 2012
|
| DOI | 10.1186/1471-2105-13-s8-s3 |
| Pubmed ID | |
| Authors |
Adam M Smith, Wen Xu, Yao Sun, James R Faeder, G Elisabeta Marai |
| Abstract |
Rule-based modeling (RBM) is a powerful and increasingly popular approach to modeling cell signaling networks. However, novel visual tools are needed in order to make RBM accessible to a broad range of users, to make specification of models less error prone, and to improve workflows. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 33% |
| United States | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 3% |
| Germany | 1 | 1% |
| Portugal | 1 | 1% |
| Russia | 1 | 1% |
| United Kingdom | 1 | 1% |
| Unknown | 67 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 21% |
| Student > Bachelor | 14 | 19% |
| Researcher | 13 | 18% |
| Student > Master | 10 | 14% |
| Professor > Associate Professor | 7 | 10% |
| Other | 11 | 15% |
| Unknown | 3 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 25 | 34% |
| Computer Science | 13 | 18% |
| Biochemistry, Genetics and Molecular Biology | 8 | 11% |
| Chemistry | 5 | 7% |
| Engineering | 5 | 7% |
| Other | 10 | 14% |
| Unknown | 7 | 10% |
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 24 May 2012.
All research outputs
#7,418,252
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#2,916
of 7,387 outputs
Outputs of similar age
#53,070
of 165,232 outputs
Outputs of similar age from BMC Bioinformatics
#44
of 103 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 7,387 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 58% 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 165,232 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 66% of its contemporaries.
We're also able to compare this research output to 103 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.