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X Demographics
Mendeley readers
Attention Score in Context
| Title |
KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images
|
|---|---|
| Published in |
Journal of Cheminformatics, June 2019
|
| DOI | 10.1186/s13321-019-0364-5 |
| Pubmed ID | |
| Authors |
Isidro Cortés-Ciriano, Andreas Bender |
X Demographics
The data shown below were collected from the profiles of 13 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 | 8% |
| India | 1 | 8% |
| Spain | 1 | 8% |
| Sweden | 1 | 8% |
| United Kingdom | 1 | 8% |
| Japan | 1 | 8% |
| Netherlands | 1 | 8% |
| Unknown | 6 | 46% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 6 | 46% |
| Members of the public | 5 | 38% |
| Practitioners (doctors, other healthcare professionals) | 1 | 8% |
| Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 81 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 17 | 21% |
| Student > Ph. D. Student | 14 | 17% |
| Student > Master | 8 | 10% |
| Other | 5 | 6% |
| Student > Bachelor | 4 | 5% |
| Other | 12 | 15% |
| Unknown | 21 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 12 | 15% |
| Computer Science | 11 | 14% |
| Biochemistry, Genetics and Molecular Biology | 11 | 14% |
| Agricultural and Biological Sciences | 7 | 9% |
| Engineering | 6 | 7% |
| Other | 8 | 10% |
| Unknown | 26 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 26 June 2019.
All research outputs
#5,028,811
of 24,143,470 outputs
Outputs from Journal of Cheminformatics
#456
of 891 outputs
Outputs of similar age
#96,386
of 355,770 outputs
Outputs of similar age from Journal of Cheminformatics
#10
of 18 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% 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 is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
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 355,770 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 18 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 50% of its contemporaries.