The data shown below were collected from the profiles of 30 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
| Title |
A ligand-based computational drug repurposing pipeline using KNIME and Programmatic Data Access: case studies for rare diseases and COVID-19
|
|---|---|
| Published in |
Journal of Cheminformatics, November 2020
|
| DOI | 10.1186/s13321-020-00474-z |
| Pubmed ID | |
| Authors |
Alzbeta Tuerkova, Barbara Zdrazil |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 7% |
| India | 2 | 7% |
| Switzerland | 1 | 3% |
| Australia | 1 | 3% |
| Brazil | 1 | 3% |
| United Kingdom | 1 | 3% |
| Spain | 1 | 3% |
| Denmark | 1 | 3% |
| Unknown | 20 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 17 | 57% |
| Scientists | 11 | 37% |
| Science communicators (journalists, bloggers, editors) | 2 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 74 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 18% |
| Student > Ph. D. Student | 10 | 14% |
| Student > Master | 9 | 12% |
| Other | 4 | 5% |
| Student > Bachelor | 4 | 5% |
| Other | 11 | 15% |
| Unknown | 23 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 13 | 18% |
| Pharmacology, Toxicology and Pharmaceutical Science | 10 | 14% |
| Biochemistry, Genetics and Molecular Biology | 5 | 7% |
| Medicine and Dentistry | 4 | 5% |
| Computer Science | 3 | 4% |
| Other | 14 | 19% |
| Unknown | 25 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 29. 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 21 November 2021.
All research outputs
#1,415,510
of 26,378,648 outputs
Outputs from Journal of Cheminformatics
#70
of 1,018 outputs
Outputs of similar age
#37,648
of 534,602 outputs
Outputs of similar age from Journal of Cheminformatics
#4
of 14 outputs
Altmetric has tracked 26,378,648 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,018 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.8. 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 534,602 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 92% of its contemporaries.
We're also able to compare this research output to 14 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 71% of its contemporaries.