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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Prediction of Drug Combinations by Integrating Molecular and Pharmacological Data
|
|---|---|
| Published in |
PLoS Computational Biology, December 2011
|
| DOI | 10.1371/journal.pcbi.1002323 |
| Pubmed ID | |
| Authors |
Xing-Ming Zhao, Murat Iskar, Georg Zeller, Michael Kuhn, Vera van Noort, Peer Bork |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 264 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 11 | 4% |
| United Kingdom | 5 | 2% |
| Germany | 4 | 2% |
| China | 2 | <1% |
| Korea, Republic of | 2 | <1% |
| Portugal | 1 | <1% |
| India | 1 | <1% |
| Slovenia | 1 | <1% |
| Netherlands | 1 | <1% |
| Other | 4 | 2% |
| Unknown | 232 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 80 | 30% |
| Researcher | 53 | 20% |
| Student > Master | 33 | 13% |
| Professor > Associate Professor | 18 | 7% |
| Student > Bachelor | 14 | 5% |
| Other | 36 | 14% |
| Unknown | 30 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 98 | 37% |
| Computer Science | 43 | 16% |
| Medicine and Dentistry | 24 | 9% |
| Biochemistry, Genetics and Molecular Biology | 18 | 7% |
| Chemistry | 14 | 5% |
| Other | 26 | 10% |
| Unknown | 41 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 19. 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 16 July 2020.
All research outputs
#1,968,019
of 25,837,817 outputs
Outputs from PLoS Computational Biology
#1,723
of 9,027 outputs
Outputs of similar age
#13,434
of 252,738 outputs
Outputs of similar age from PLoS Computational Biology
#7
of 120 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,027 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 well, scoring higher than 80% 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 252,738 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 94% of its contemporaries.
We're also able to compare this research output to 120 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 94% of its contemporaries.