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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using set theory to reduce redundancy in pathway sets
|
|---|---|
| Published in |
BMC Bioinformatics, October 2018
|
| DOI | 10.1186/s12859-018-2355-3 |
| Pubmed ID | |
| Authors |
Ruth Alexandra Stoney, Jean-Marc Schwartz, David L Robertson, Goran Nenadic |
X Demographics
The data shown below were collected from the profiles of 10 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 States | 4 | 40% |
| Portugal | 1 | 10% |
| Spain | 1 | 10% |
| Qatar | 1 | 10% |
| Unknown | 3 | 30% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 8 | 80% |
| Members of the public | 2 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 49 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 24% |
| Researcher | 12 | 24% |
| Student > Bachelor | 5 | 10% |
| Student > Master | 4 | 8% |
| Student > Doctoral Student | 2 | 4% |
| Other | 6 | 12% |
| Unknown | 8 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 12 | 24% |
| Biochemistry, Genetics and Molecular Biology | 11 | 22% |
| Computer Science | 7 | 14% |
| Medicine and Dentistry | 4 | 8% |
| Immunology and Microbiology | 2 | 4% |
| Other | 3 | 6% |
| Unknown | 10 | 20% |
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 14 August 2023.
All research outputs
#2,552,650
of 25,342,911 outputs
Outputs from BMC Bioinformatics
#658
of 7,676 outputs
Outputs of similar age
#51,628
of 356,969 outputs
Outputs of similar age from BMC Bioinformatics
#14
of 135 outputs
Altmetric has tracked 25,342,911 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 7,676 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 done particularly well, scoring higher than 91% 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 356,969 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 135 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 90% of its contemporaries.