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X Demographics
Mendeley readers
Attention Score in Context
| Title |
TADA—a machine learning tool for functional annotation-based prioritisation of pathogenic CNVs
|
|---|---|
| Published in |
Genome Biology, March 2022
|
| DOI | 10.1186/s13059-022-02631-z |
| Pubmed ID | |
| Authors |
Jakob Hertzberg, Stefan Mundlos, Martin Vingron, Giuseppe Gallone |
X Demographics
The data shown below were collected from the profiles of 39 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 9 | 23% |
| United States | 5 | 13% |
| India | 4 | 10% |
| United Kingdom | 3 | 8% |
| Sweden | 1 | 3% |
| Japan | 1 | 3% |
| Canada | 1 | 3% |
| Italy | 1 | 3% |
| Switzerland | 1 | 3% |
| Other | 2 | 5% |
| Unknown | 11 | 28% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 21 | 54% |
| Scientists | 16 | 41% |
| Science communicators (journalists, bloggers, editors) | 2 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 27 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 19% |
| Student > Ph. D. Student | 3 | 11% |
| Student > Bachelor | 2 | 7% |
| Student > Postgraduate | 1 | 4% |
| Unknown | 16 | 59% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 22% |
| Computer Science | 2 | 7% |
| Agricultural and Biological Sciences | 1 | 4% |
| Social Sciences | 1 | 4% |
| Engineering | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 16 | 59% |
Attention Score in Context
This research output has an Altmetric Attention Score of 21. 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 29 December 2022.
All research outputs
#1,846,683
of 25,816,430 outputs
Outputs from Genome Biology
#1,530
of 4,520 outputs
Outputs of similar age
#44,341
of 453,006 outputs
Outputs of similar age from Genome Biology
#41
of 74 outputs
Altmetric has tracked 25,816,430 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,520 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.5. This one has gotten more attention than average, scoring higher than 66% 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 453,006 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 90% of its contemporaries.
We're also able to compare this research output to 74 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.