You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
PSCAN: Spatial scan tests guided by protein structures improve complex disease gene discovery and signal variant detection
|
|---|---|
| Published in |
Genome Biology, August 2020
|
| DOI | 10.1186/s13059-020-02121-0 |
| Pubmed ID | |
| Authors |
Zheng-Zheng Tang, Gregory R. Sliwoski, Guanhua Chen, Bowen Jin, William S. Bush, Bingshan Li, John A. Capra |
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 % |
|---|---|---|
| Sweden | 1 | 20% |
| United States | 1 | 20% |
| United Kingdom | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 1 | 20% |
| Science communicators (journalists, bloggers, editors) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 25% |
| Unspecified | 4 | 17% |
| Student > Master | 3 | 13% |
| Researcher | 2 | 8% |
| Student > Bachelor | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 7 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 4 | 17% |
| Biochemistry, Genetics and Molecular Biology | 4 | 17% |
| Computer Science | 3 | 13% |
| Environmental Science | 1 | 4% |
| Agricultural and Biological Sciences | 1 | 4% |
| Other | 3 | 13% |
| Unknown | 8 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 September 2020.
All research outputs
#15,232,080
of 25,837,817 outputs
Outputs from Genome Biology
#3,917
of 4,513 outputs
Outputs of similar age
#212,857
of 428,125 outputs
Outputs of similar age from Genome Biology
#87
of 92 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,513 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.7. This one is in the 12th percentile – i.e., 12% 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 428,125 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 92 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.