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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Reverse engineering directed gene regulatory networks from transcriptomics and proteomics data of biomining bacterial communities with approximate Bayesian computation and steady-state signalling simulations
|
|---|---|
| Published in |
BMC Bioinformatics, January 2020
|
| DOI | 10.1186/s12859-019-3337-9 |
| Pubmed ID | |
| Authors |
Antoine Buetti-Dinh, Malte Herold, Stephan Christel, Mohamed El Hajjami, Francesco Delogu, Olga Ilie, Sören Bellenberg, Paul Wilmes, Ansgar Poetsch, Wolfgang Sand, Mario Vera, Igor V. Pivkin, Ran Friedman, Mark Dopson |
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 % |
|---|---|---|
| United Kingdom | 3 | 75% |
| Andorra | 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 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 48 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 21% |
| Researcher | 7 | 15% |
| Student > Master | 6 | 13% |
| Student > Doctoral Student | 3 | 6% |
| Student > Bachelor | 3 | 6% |
| Other | 3 | 6% |
| Unknown | 16 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 21% |
| Biochemistry, Genetics and Molecular Biology | 8 | 17% |
| Computer Science | 5 | 10% |
| Engineering | 3 | 6% |
| Business, Management and Accounting | 1 | 2% |
| Other | 4 | 8% |
| Unknown | 17 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 January 2020.
All research outputs
#13,593,571
of 23,189,371 outputs
Outputs from BMC Bioinformatics
#4,234
of 7,345 outputs
Outputs of similar age
#219,881
of 455,694 outputs
Outputs of similar age from BMC Bioinformatics
#92
of 187 outputs
Altmetric has tracked 23,189,371 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,345 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 42nd percentile – i.e., 42% 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 455,694 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 51% of its contemporaries.
We're also able to compare this research output to 187 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 50% of its contemporaries.