| Title |
PathVisio 3: An Extendable Pathway Analysis Toolbox
|
|---|---|
| Published in |
PLoS Computational Biology, February 2015
|
| DOI | 10.1371/journal.pcbi.1004085 |
| Pubmed ID | |
| Authors |
Martina Kutmon, Martijn P. van Iersel, Anwesha Bohler, Thomas Kelder, Nuno Nunes, Alexander R. Pico, Chris T. Evelo |
X Demographics
The data shown below were collected from the profiles of 45 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 | 9 | 20% |
| Netherlands | 4 | 9% |
| Germany | 4 | 9% |
| France | 2 | 4% |
| India | 2 | 4% |
| Spain | 2 | 4% |
| Japan | 1 | 2% |
| Canada | 1 | 2% |
| Switzerland | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 18 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 22 | 49% |
| Members of the public | 22 | 49% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 331 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 4 | 1% |
| United States | 2 | <1% |
| Brazil | 1 | <1% |
| Sweden | 1 | <1% |
| Colombia | 1 | <1% |
| Canada | 1 | <1% |
| Iran, Islamic Republic of | 1 | <1% |
| Mexico | 1 | <1% |
| South Africa | 1 | <1% |
| Other | 4 | 1% |
| Unknown | 314 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 79 | 24% |
| Researcher | 61 | 18% |
| Student > Master | 47 | 14% |
| Student > Bachelor | 38 | 11% |
| Professor | 13 | 4% |
| Other | 41 | 12% |
| Unknown | 52 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 100 | 30% |
| Biochemistry, Genetics and Molecular Biology | 85 | 26% |
| Computer Science | 18 | 5% |
| Medicine and Dentistry | 10 | 3% |
| Neuroscience | 9 | 3% |
| Other | 52 | 16% |
| Unknown | 57 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 45. 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 03 November 2021.
All research outputs
#927,183
of 25,450,869 outputs
Outputs from PLoS Computational Biology
#702
of 8,978 outputs
Outputs of similar age
#11,398
of 269,904 outputs
Outputs of similar age from PLoS Computational Biology
#17
of 129 outputs
Altmetric has tracked 25,450,869 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,978 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done particularly well, scoring higher than 92% 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 269,904 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 129 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.