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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The use of 2D fingerprint methods to support the assessment of structural similarity in orphan drug legislation
|
|---|---|
| Published in |
Journal of Cheminformatics, February 2014
|
| DOI | 10.1186/1758-2946-6-5 |
| Pubmed ID | |
| Authors |
Pedro Franco, Nuria Porta, John D Holliday, Peter Willett |
| Abstract |
In the European Union, medicines are authorised for some rare disease only if they are judged to be dissimilar to authorised orphan drugs for that disease. This paper describes the use of 2D fingerprints to show the extent of the relationship between computed levels of structural similarity for pairs of molecules and expert judgments of the similarities of those pairs. The resulting relationship can be used to provide input to the assessment of new active compounds for which orphan drug authorisation is being sought. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 17% |
| Brazil | 1 | 17% |
| United Kingdom | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 50% |
| Members of the public | 2 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 3 | 4% |
| Romania | 1 | 1% |
| Brazil | 1 | 1% |
| Unknown | 66 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 18% |
| Researcher | 13 | 18% |
| Student > Master | 11 | 15% |
| Student > Bachelor | 9 | 13% |
| Student > Doctoral Student | 6 | 8% |
| Other | 13 | 18% |
| Unknown | 6 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 16 | 23% |
| Agricultural and Biological Sciences | 9 | 13% |
| Computer Science | 8 | 11% |
| Medicine and Dentistry | 8 | 11% |
| Social Sciences | 5 | 7% |
| Other | 16 | 23% |
| Unknown | 9 | 13% |
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 22 December 2022.
All research outputs
#2,355,098
of 24,143,470 outputs
Outputs from Journal of Cheminformatics
#215
of 891 outputs
Outputs of similar age
#28,065
of 316,284 outputs
Outputs of similar age from Journal of Cheminformatics
#3
of 10 outputs
Altmetric has tracked 24,143,470 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 891 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one has done well, scoring higher than 75% 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 316,284 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 91% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 7 of them.