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X Demographics
Mendeley readers
Attention Score in Context
| Title |
In-silico predictive mutagenicity model generation using supervised learning approaches
|
|---|---|
| Published in |
Journal of Cheminformatics, May 2012
|
| DOI | 10.1186/1758-2946-4-10 |
| Pubmed ID | |
| Authors |
Abhik Seal, Anurag Passi, UC Abdul Jaleel, Open Source Drug Discovery Consortium, David J Wild |
X Demographics
The data shown below were collected from the profiles of 4 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 | 2 | 50% |
| Germany | 1 | 25% |
| India | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
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 % |
|---|---|---|
| India | 2 | 3% |
| France | 1 | 1% |
| Germany | 1 | 1% |
| Brazil | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 65 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 17% |
| Researcher | 12 | 17% |
| Student > Master | 11 | 15% |
| Student > Bachelor | 8 | 11% |
| Professor > Associate Professor | 5 | 7% |
| Other | 12 | 17% |
| Unknown | 11 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 14 | 20% |
| Agricultural and Biological Sciences | 13 | 18% |
| Computer Science | 8 | 11% |
| Medicine and Dentistry | 5 | 7% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 6% |
| Other | 9 | 13% |
| Unknown | 18 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 10 March 2014.
All research outputs
#2,316,466
of 22,665,794 outputs
Outputs from Journal of Cheminformatics
#228
of 825 outputs
Outputs of similar age
#15,248
of 163,696 outputs
Outputs of similar age from Journal of Cheminformatics
#2
of 8 outputs
Altmetric has tracked 22,665,794 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 825 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one has gotten more attention than average, scoring higher than 72% 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 163,696 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 90% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.