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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Benchmarking workflows to assess performance and suitability of germline variant calling pipelines in clinical diagnostic assays
|
|---|---|
| Published in |
BMC Bioinformatics, February 2021
|
| DOI | 10.1186/s12859-020-03934-3 |
| Pubmed ID | |
| Authors |
Vandhana Krishnan, Sowmithri Utiramerur, Zena Ng, Somalee Datta, Michael P. Snyder, Euan A. Ashley |
X Demographics
The data shown below were collected from the profiles of 14 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 Kingdom | 3 | 21% |
| United States | 3 | 21% |
| India | 1 | 7% |
| Germany | 1 | 7% |
| Sweden | 1 | 7% |
| Unknown | 5 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 11 | 79% |
| Members of the public | 3 | 21% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 44 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 32% |
| Student > Ph. D. Student | 5 | 11% |
| Other | 4 | 9% |
| Student > Bachelor | 2 | 5% |
| Student > Master | 2 | 5% |
| Other | 4 | 9% |
| Unknown | 13 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 13 | 30% |
| Agricultural and Biological Sciences | 7 | 16% |
| Medicine and Dentistry | 7 | 16% |
| Computer Science | 3 | 7% |
| Engineering | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 13 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 05 April 2022.
All research outputs
#5,807,463
of 23,493,900 outputs
Outputs from BMC Bioinformatics
#2,086
of 7,397 outputs
Outputs of similar age
#126,699
of 419,252 outputs
Outputs of similar age from BMC Bioinformatics
#51
of 137 outputs
Altmetric has tracked 23,493,900 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,397 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 71% 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 419,252 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 69% of its contemporaries.
We're also able to compare this research output to 137 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.