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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A machine learning-based chemoproteomic approach to identify drug targets and binding sites in complex proteomes
|
|---|---|
| Published in |
Nature Communications, August 2020
|
| DOI | 10.1038/s41467-020-18071-x |
| Pubmed ID | |
| Authors |
Ilaria Piazza, Nigel Beaton, Roland Bruderer, Thomas Knobloch, Crystel Barbisan, Lucie Chandat, Alexander Sudau, Isabella Siepe, Oliver Rinner, Natalie de Souza, Paola Picotti, Lukas Reiter |
X Demographics
The data shown below were collected from the profiles of 56 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 | 16% |
| Switzerland | 8 | 14% |
| United Kingdom | 3 | 5% |
| Germany | 2 | 4% |
| Netherlands | 2 | 4% |
| India | 2 | 4% |
| South Africa | 1 | 2% |
| Italy | 1 | 2% |
| Portugal | 1 | 2% |
| Other | 4 | 7% |
| Unknown | 23 | 41% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 40 | 71% |
| Scientists | 11 | 20% |
| Science communicators (journalists, bloggers, editors) | 4 | 7% |
| Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 245 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 245 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 56 | 23% |
| Researcher | 56 | 23% |
| Student > Master | 22 | 9% |
| Student > Bachelor | 16 | 7% |
| Other | 7 | 3% |
| Other | 21 | 9% |
| Unknown | 67 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 75 | 31% |
| Chemistry | 38 | 16% |
| Agricultural and Biological Sciences | 18 | 7% |
| Computer Science | 6 | 2% |
| Pharmacology, Toxicology and Pharmaceutical Science | 6 | 2% |
| Other | 29 | 12% |
| Unknown | 73 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 153. 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 April 2023.
All research outputs
#273,862
of 25,743,152 outputs
Outputs from Nature Communications
#4,020
of 58,308 outputs
Outputs of similar age
#8,447
of 426,358 outputs
Outputs of similar age from Nature Communications
#128
of 1,524 outputs
Altmetric has tracked 25,743,152 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 58,308 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 55.4. This one has done particularly well, scoring higher than 93% 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 426,358 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 98% of its contemporaries.
We're also able to compare this research output to 1,524 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 91% of its contemporaries.