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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Computational toxicology using the OpenTox application programming interface and Bioclipse
|
|---|---|
| Published in |
BMC Research Notes, November 2011
|
| DOI | 10.1186/1756-0500-4-487 |
| Pubmed ID | |
| Authors |
Egon L Willighagen, Nina Jeliazkova, Barry Hardy, Roland C Grafström, Ola Spjuth |
| Abstract |
Toxicity is a complex phenomenon involving the potential adverse effect on a range of biological functions. Predicting toxicity involves using a combination of experimental data (endpoints) and computational methods to generate a set of predictive models. Such models rely strongly on being able to integrate information from many sources. The required integration of biological and chemical information sources requires, however, a common language to express our knowledge ontologically, and interoperating services to build reliable predictive toxicology applications. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 3 | 4% |
| Netherlands | 2 | 3% |
| Bulgaria | 2 | 3% |
| United Kingdom | 2 | 3% |
| Brazil | 1 | 1% |
| Germany | 1 | 1% |
| Denmark | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 60 | 82% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 18 | 25% |
| Student > Ph. D. Student | 17 | 23% |
| Other | 7 | 10% |
| Student > Master | 7 | 10% |
| Professor > Associate Professor | 5 | 7% |
| Other | 11 | 15% |
| Unknown | 8 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 18 | 25% |
| Chemistry | 11 | 15% |
| Agricultural and Biological Sciences | 10 | 14% |
| Pharmacology, Toxicology and Pharmaceutical Science | 6 | 8% |
| Biochemistry, Genetics and Molecular Biology | 5 | 7% |
| Other | 15 | 21% |
| Unknown | 8 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 18 February 2017.
All research outputs
#1,930,153
of 24,143,470 outputs
Outputs from BMC Research Notes
#230
of 4,364 outputs
Outputs of similar age
#9,675
of 146,061 outputs
Outputs of similar age from BMC Research Notes
#3
of 63 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 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,364 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.9. 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 146,061 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 93% of its contemporaries.
We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.