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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Evaluation of statistical approaches for association testing in noisy drug screening data
|
|---|---|
| Published in |
BMC Bioinformatics, May 2022
|
| DOI | 10.1186/s12859-022-04693-z |
| Pubmed ID | |
| Authors |
Petr Smirnov, Ian Smith, Zhaleh Safikhani, Wail Ba-alawi, Farnoosh Khodakarami, Eva Lin, Yihong Yu, Scott Martin, Janosch Ortmann, Tero Aittokallio, Marc Hafner, Benjamin Haibe-Kains |
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% |
| Finland | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 40% |
| Scientists | 2 | 40% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 2 | 18% |
| Professor | 1 | 9% |
| Student > Postgraduate | 1 | 9% |
| Researcher | 1 | 9% |
| Unknown | 6 | 55% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 2 | 18% |
| Biochemistry, Genetics and Molecular Biology | 2 | 18% |
| Mathematics | 1 | 9% |
| Unknown | 6 | 55% |
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 30 November 2022.
All research outputs
#16,681,672
of 25,837,817 outputs
Outputs from BMC Bioinformatics
#5,087
of 7,763 outputs
Outputs of similar age
#231,443
of 446,573 outputs
Outputs of similar age from BMC Bioinformatics
#95
of 145 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,763 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one is in the 30th percentile – i.e., 30% 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 446,573 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% 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 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.