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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The Process-Interaction-Model: a common representation of rule-based and logical models allows studying signal transduction on different levels of detail
|
|---|---|
| Published in |
BMC Bioinformatics, September 2012
|
| DOI | 10.1186/1471-2105-13-251 |
| Pubmed ID | |
| Authors |
Katrin Kolczyk, Regina Samaga, Holger Conzelmann, Sebastian Mirschel, Carsten Conradi |
| Abstract |
Signaling systems typically involve large, structured molecules each consisting of a large number of subunits called molecule domains. In modeling such systems these domains can be considered as the main players. In order to handle the resulting combinatorial complexity, rule-based modeling has been established as the tool of choice. In contrast to the detailed quantitative rule-based modeling, qualitative modeling approaches like logical modeling rely solely on the network structure and are particularly useful for analyzing structural and functional properties of signaling systems. |
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 % |
|---|---|---|
| Japan | 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 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 5% |
| United States | 1 | 5% |
| Unknown | 20 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 27% |
| Student > Ph. D. Student | 6 | 27% |
| Professor > Associate Professor | 3 | 14% |
| Student > Master | 3 | 14% |
| Student > Bachelor | 2 | 9% |
| Other | 2 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 7 | 32% |
| Agricultural and Biological Sciences | 7 | 32% |
| Engineering | 3 | 14% |
| Chemical Engineering | 2 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 5% |
| Other | 2 | 9% |
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 01 October 2012.
All research outputs
#18,316,001
of 22,679,690 outputs
Outputs from BMC Bioinformatics
#6,281
of 7,250 outputs
Outputs of similar age
#130,758
of 172,156 outputs
Outputs of similar age from BMC Bioinformatics
#85
of 106 outputs
Altmetric has tracked 22,679,690 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 7,250 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 5th percentile – i.e., 5% 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 172,156 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 106 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.