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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine learning approaches to optimize small-molecule inhibitors for RNA targeting
|
|---|---|
| Published in |
Journal of Cheminformatics, February 2022
|
| DOI | 10.1186/s13321-022-00583-x |
| Pubmed ID | |
| Authors |
Hadar Grimberg, Vinay S. Tiwari, Benjamin Tam, Lihi Gur-Arie, Daniela Gingold, Lea Polachek, Barak Akabayov |
X Demographics
The data shown below were collected from the profiles of 38 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 7 | 18% |
| Israel | 2 | 5% |
| Mexico | 1 | 3% |
| United Kingdom | 1 | 3% |
| Canada | 1 | 3% |
| Korea, Democratic People's Republic of | 1 | 3% |
| Unknown | 25 | 66% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 30 | 79% |
| Scientists | 7 | 18% |
| Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 32 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 16% |
| Student > Master | 4 | 13% |
| Student > Ph. D. Student | 4 | 13% |
| Other | 1 | 3% |
| Student > Bachelor | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 16 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 13% |
| Chemistry | 3 | 9% |
| Computer Science | 3 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 6% |
| Medicine and Dentistry | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 18 | 56% |
Attention Score in Context
This research output has an Altmetric Attention Score of 23. 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 17 March 2022.
All research outputs
#1,698,403
of 25,959,914 outputs
Outputs from Journal of Cheminformatics
#115
of 985 outputs
Outputs of similar age
#41,587
of 521,805 outputs
Outputs of similar age from Journal of Cheminformatics
#4
of 17 outputs
Altmetric has tracked 25,959,914 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 985 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 well, scoring higher than 88% 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 521,805 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 17 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.