| Title |
BioTransformer: a comprehensive computational tool for small molecule metabolism prediction and metabolite identification
|
|---|---|
| Published in |
Journal of Cheminformatics, January 2019
|
| DOI | 10.1186/s13321-018-0324-5 |
| Pubmed ID | |
| Authors |
Yannick Djoumbou-Feunang, Jarlei Fiamoncini, Alberto Gil-de-la-Fuente, Russell Greiner, Claudine Manach, David S. Wishart |
X Demographics
The data shown below were collected from the profiles of 66 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 | 12 | 18% |
| Spain | 3 | 5% |
| Sweden | 3 | 5% |
| France | 3 | 5% |
| Canada | 2 | 3% |
| Netherlands | 2 | 3% |
| Germany | 2 | 3% |
| Israel | 2 | 3% |
| Luxembourg | 2 | 3% |
| Other | 9 | 14% |
| Unknown | 26 | 39% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 37 | 56% |
| Members of the public | 24 | 36% |
| Science communicators (journalists, bloggers, editors) | 3 | 5% |
| Practitioners (doctors, other healthcare professionals) | 2 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 482 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 482 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 85 | 18% |
| Student > Ph. D. Student | 83 | 17% |
| Student > Master | 44 | 9% |
| Student > Bachelor | 44 | 9% |
| Student > Doctoral Student | 20 | 4% |
| Other | 68 | 14% |
| Unknown | 138 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 83 | 17% |
| Biochemistry, Genetics and Molecular Biology | 66 | 14% |
| Pharmacology, Toxicology and Pharmaceutical Science | 38 | 8% |
| Agricultural and Biological Sciences | 36 | 7% |
| Environmental Science | 18 | 4% |
| Other | 69 | 14% |
| Unknown | 172 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 48. 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 02 September 2023.
All research outputs
#867,077
of 25,391,701 outputs
Outputs from Journal of Cheminformatics
#22
of 961 outputs
Outputs of similar age
#19,889
of 443,719 outputs
Outputs of similar age from Journal of Cheminformatics
#2
of 30 outputs
Altmetric has tracked 25,391,701 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 961 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.1. This one has done particularly well, scoring higher than 97% 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 443,719 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 95% of its contemporaries.
We're also able to compare this research output to 30 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.