| 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
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 13% |
| India | 3 | 10% |
| United Kingdom | 3 | 10% |
| Australia | 1 | 3% |
| Sweden | 1 | 3% |
| Spain | 1 | 3% |
| Switzerland | 1 | 3% |
| Brazil | 1 | 3% |
| Denmark | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 14 | 47% |
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 | 9 | 12% |
| Student > Master | 9 | 12% |
| Other | 4 | 5% |
| Student > Bachelor | 4 | 5% |
| Other | 12 | 16% |
| Unknown | 23 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 12 | 16% |
| Pharmacology, Toxicology and Pharmaceutical Science | 10 | 14% |
| Biochemistry, Genetics and Molecular Biology | 5 | 7% |
| Medicine and Dentistry | 4 | 5% |
| Nursing and Health Professions | 3 | 4% |
| Other | 15 | 20% |
| Unknown | 25 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 30. 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
#1,299,453
of 25,163,238 outputs
Outputs from Journal of Cheminformatics
#63
of 946 outputs
Outputs of similar age
#34,934
of 522,906 outputs
Outputs of similar age from Journal of Cheminformatics
#4
of 14 outputs
Altmetric has tracked 25,163,238 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 946 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. 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 522,906 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 93% 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 done well, scoring higher than 78% of its contemporaries.