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X Demographics
Mendeley readers
Attention Score in Context
| Title |
On the Integration of In Silico Drug Design Methods for Drug Repurposing
|
|---|---|
| Published in |
Frontiers in Pharmacology, May 2017
|
| DOI | 10.3389/fphar.2017.00298 |
| Pubmed ID | |
| Authors |
Eric March-Vila, Luca Pinzi, Noé Sturm, Annachiara Tinivella, Ola Engkvist, Hongming Chen, Giulio Rastelli |
| Abstract |
Drug repurposing has become an important branch of drug discovery. Several computational approaches that help to uncover new repurposing opportunities and aid the discovery process have been put forward, or adapted from previous applications. A number of successful examples are now available. Overall, future developments will greatly benefit from integration of different methods, approaches and disciplines. Steps forward in this direction are expected to help to clarify, and therefore to rationally predict, new drug-target, target-disease, and ultimately drug-disease associations. |
X Demographics
The data shown below were collected from the profiles of 3 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 | 1 | 33% |
| Switzerland | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 342 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 342 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 50 | 15% |
| Student > Ph. D. Student | 44 | 13% |
| Student > Bachelor | 44 | 13% |
| Student > Master | 35 | 10% |
| Student > Doctoral Student | 18 | 5% |
| Other | 55 | 16% |
| Unknown | 96 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 52 | 15% |
| Pharmacology, Toxicology and Pharmaceutical Science | 45 | 13% |
| Chemistry | 42 | 12% |
| Computer Science | 20 | 6% |
| Agricultural and Biological Sciences | 14 | 4% |
| Other | 56 | 16% |
| Unknown | 113 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 19 March 2020.
All research outputs
#2,265,694
of 22,974,684 outputs
Outputs from Frontiers in Pharmacology
#866
of 16,256 outputs
Outputs of similar age
#45,096
of 313,690 outputs
Outputs of similar age from Frontiers in Pharmacology
#28
of 244 outputs
Altmetric has tracked 22,974,684 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 16,256 research outputs from this source. They receive a mean Attention Score of 5.0. This one has done particularly well, scoring higher than 94% 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 313,690 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 244 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.