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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Predicting drug side-effect profiles: a chemical fragment-based approach
|
|---|---|
| Published in |
BMC Bioinformatics, May 2011
|
| DOI | 10.1186/1471-2105-12-169 |
| Pubmed ID | |
| Authors |
Edouard Pauwels, Véronique Stoven, Yoshihiro Yamanishi |
| Abstract |
Drug side-effects, or adverse drug reactions, have become a major public health concern. It is one of the main causes of failure in the process of drug development, and of drug withdrawal once they have reached the market. Therefore, in silico prediction of potential side-effects early in the drug discovery process, before reaching the clinical stages, is of great interest to improve this long and expensive process and to provide new efficient and safe therapies for patients. |
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 % |
|---|---|---|
| United Kingdom | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 168 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 3 | 2% |
| United States | 2 | 1% |
| Japan | 2 | 1% |
| Finland | 1 | <1% |
| United Kingdom | 1 | <1% |
| China | 1 | <1% |
| Brazil | 1 | <1% |
| Germany | 1 | <1% |
| Nigeria | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 155 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 39 | 23% |
| Student > Master | 36 | 21% |
| Researcher | 22 | 13% |
| Student > Bachelor | 14 | 8% |
| Student > Postgraduate | 9 | 5% |
| Other | 25 | 15% |
| Unknown | 23 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 34 | 20% |
| Computer Science | 30 | 18% |
| Chemistry | 20 | 12% |
| Biochemistry, Genetics and Molecular Biology | 13 | 8% |
| Medicine and Dentistry | 13 | 8% |
| Other | 31 | 18% |
| Unknown | 27 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 25 January 2024.
All research outputs
#6,979,498
of 25,233,554 outputs
Outputs from BMC Bioinformatics
#2,474
of 7,661 outputs
Outputs of similar age
#37,036
of 117,825 outputs
Outputs of similar age from BMC Bioinformatics
#26
of 88 outputs
Altmetric has tracked 25,233,554 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 7,661 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 66% 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 117,825 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 68% of its contemporaries.
We're also able to compare this research output to 88 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 69% of its contemporaries.