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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Drug-induced cell viability prediction from LINCS-L1000 through WRFEN-XGBoost algorithm
|
|---|---|
| Published in |
BMC Bioinformatics, January 2021
|
| DOI | 10.1186/s12859-020-03949-w |
| Pubmed ID | |
| Authors |
Jiaxing Lu, Ming Chen, Yufang Qin |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 20% |
| Sweden | 1 | 20% |
| United Kingdom | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 80% |
| Members of the public | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 32 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 16% |
| Researcher | 4 | 13% |
| Student > Ph. D. Student | 2 | 6% |
| Professor | 2 | 6% |
| Other | 1 | 3% |
| Other | 3 | 9% |
| Unknown | 15 | 47% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 6 | 19% |
| Engineering | 3 | 9% |
| Medicine and Dentistry | 3 | 9% |
| Mathematics | 1 | 3% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 16 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 08 January 2021.
All research outputs
#15,130,956
of 23,271,751 outputs
Outputs from BMC Bioinformatics
#5,127
of 7,368 outputs
Outputs of similar age
#288,336
of 503,379 outputs
Outputs of similar age from BMC Bioinformatics
#116
of 145 outputs
Altmetric has tracked 23,271,751 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,368 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 25th percentile – i.e., 25% 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 503,379 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 145 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.