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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Algorithmic improvements for discovery of germline copy number variants in next-generation sequencing data
|
|---|---|
| Published in |
BMC Bioinformatics, July 2022
|
| DOI | 10.1186/s12859-022-04820-w |
| Pubmed ID | |
| Authors |
Brendan O’Fallon, Jacob Durtschi, Ana Kellogg, Tracey Lewis, Devin Close, Hunter Best |
X Demographics
The data shown below were collected from the profiles of 8 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 | 2 | 25% |
| Malaysia | 1 | 13% |
| Sweden | 1 | 13% |
| India | 1 | 13% |
| Unknown | 3 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 6 | 75% |
| Members of the public | 2 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 18 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 22% |
| Student > Bachelor | 3 | 17% |
| Student > Ph. D. Student | 2 | 11% |
| Student > Postgraduate | 2 | 11% |
| Researcher | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 5 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 7 | 39% |
| Agricultural and Biological Sciences | 4 | 22% |
| Neuroscience | 1 | 6% |
| Medicine and Dentistry | 1 | 6% |
| Unknown | 5 | 28% |
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 24 July 2022.
All research outputs
#13,819,512
of 24,137,933 outputs
Outputs from BMC Bioinformatics
#3,894
of 7,505 outputs
Outputs of similar age
#168,956
of 422,796 outputs
Outputs of similar age from BMC Bioinformatics
#52
of 146 outputs
Altmetric has tracked 24,137,933 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,505 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 45th percentile – i.e., 45% 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 422,796 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 59% of its contemporaries.
We're also able to compare this research output to 146 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 59% of its contemporaries.