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X Demographics
Mendeley readers
Attention Score in Context
| Title |
ADMET evaluation in drug discovery. 20. Prediction of breast cancer resistance protein inhibition through machine learning
|
|---|---|
| Published in |
Journal of Cheminformatics, March 2020
|
| DOI | 10.1186/s13321-020-00421-y |
| Pubmed ID | |
| Authors |
Dejun Jiang, Tailong Lei, Zhe Wang, Chao Shen, Dongsheng Cao, Tingjun Hou |
X Demographics
The data shown below were collected from the profiles of 9 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 | 1 | 11% |
| Japan | 1 | 11% |
| Unknown | 7 | 78% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 56% |
| Scientists | 2 | 22% |
| Science communicators (journalists, bloggers, editors) | 2 | 22% |
Mendeley readers
The data shown below were compiled from readership statistics for 101 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 101 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 13 | 13% |
| Researcher | 13 | 13% |
| Student > Ph. D. Student | 11 | 11% |
| Student > Bachelor | 7 | 7% |
| Other | 4 | 4% |
| Other | 11 | 11% |
| Unknown | 42 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 12 | 12% |
| Biochemistry, Genetics and Molecular Biology | 11 | 11% |
| Engineering | 6 | 6% |
| Pharmacology, Toxicology and Pharmaceutical Science | 6 | 6% |
| Computer Science | 5 | 5% |
| Other | 14 | 14% |
| Unknown | 47 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 13 January 2021.
All research outputs
#7,955,341
of 25,837,817 outputs
Outputs from Journal of Cheminformatics
#596
of 981 outputs
Outputs of similar age
#143,139
of 389,132 outputs
Outputs of similar age from Journal of Cheminformatics
#20
of 23 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 981 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 10.0. This one is in the 38th percentile – i.e., 38% of its peers scored the same or lower than it.
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 389,132 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 62% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.