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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Identifying dynamical modules from genetic regulatory systems: applications to the segment polarity network
|
|---|---|
| Published in |
BMC Bioinformatics, October 2007
|
| DOI | 10.1186/1471-2105-8-413 |
| Pubmed ID | |
| Authors |
David J Irons, Nicholas AM Monk |
| Abstract |
It is widely accepted that genetic regulatory systems are 'modular', in that the whole system is made up of smaller 'subsystems' corresponding to specific biological functions. Most attempts to identify modules in genetic regulatory systems have relied on the topology of the underlying network. However, it is the temporal activity (dynamics) of genes and proteins that corresponds to biological functions, and hence it is dynamics that we focus on here for identifying subsystems. |
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% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 5% |
| United States | 2 | 5% |
| Portugal | 1 | 3% |
| Brazil | 1 | 3% |
| Germany | 1 | 3% |
| France | 1 | 3% |
| Luxembourg | 1 | 3% |
| Unknown | 29 | 76% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 34% |
| Student > Ph. D. Student | 7 | 18% |
| Student > Master | 4 | 11% |
| Professor > Associate Professor | 3 | 8% |
| Professor | 3 | 8% |
| Other | 5 | 13% |
| Unknown | 3 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 26% |
| Computer Science | 6 | 16% |
| Biochemistry, Genetics and Molecular Biology | 4 | 11% |
| Mathematics | 3 | 8% |
| Medicine and Dentistry | 3 | 8% |
| Other | 9 | 24% |
| Unknown | 3 | 8% |
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 02 February 2021.
All research outputs
#7,418,226
of 23,342,092 outputs
Outputs from BMC Bioinformatics
#2,915
of 7,388 outputs
Outputs of similar age
#25,526
of 77,214 outputs
Outputs of similar age from BMC Bioinformatics
#21
of 51 outputs
Altmetric has tracked 23,342,092 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 7,388 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 77,214 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 51 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.