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X Demographics
Mendeley readers
Attention Score in Context
| Title |
EXCAVATOR: detecting copy number variants from whole-exome sequencing data
|
|---|---|
| Published in |
Genome Biology, December 2013
|
| DOI | 10.1186/gb-2013-14-10-r120 |
| Pubmed ID | |
| Authors |
Alberto Magi, Lorenzo Tattini, Ingrid Cifola, Romina D’Aurizio, Matteo Benelli, Eleonora Mangano, Cristina Battaglia, Elena Bonora, Ants Kurg, Marco Seri, Pamela Magini, Betti Giusti, Giovanni Romeo, Tommaso Pippucci, Gianluca De Bellis, Rosanna Abbate, Gian Franco Gensini |
X Demographics
The data shown below were collected from the profiles of 25 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 5 | 20% |
| United States | 5 | 20% |
| United Kingdom | 2 | 8% |
| Sweden | 1 | 4% |
| Germany | 1 | 4% |
| India | 1 | 4% |
| Montenegro | 1 | 4% |
| Unknown | 9 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 18 | 72% |
| Scientists | 6 | 24% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 310 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 5 | 2% |
| United States | 4 | 1% |
| United Kingdom | 4 | 1% |
| France | 2 | <1% |
| Brazil | 2 | <1% |
| Hong Kong | 1 | <1% |
| Ghana | 1 | <1% |
| Ireland | 1 | <1% |
| Norway | 1 | <1% |
| Other | 7 | 2% |
| Unknown | 282 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 83 | 27% |
| Student > Ph. D. Student | 80 | 26% |
| Student > Master | 32 | 10% |
| Student > Bachelor | 17 | 5% |
| Student > Doctoral Student | 15 | 5% |
| Other | 45 | 15% |
| Unknown | 38 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 104 | 34% |
| Biochemistry, Genetics and Molecular Biology | 84 | 27% |
| Computer Science | 30 | 10% |
| Medicine and Dentistry | 23 | 7% |
| Engineering | 8 | 3% |
| Other | 18 | 6% |
| Unknown | 43 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 24. 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 October 2018.
All research outputs
#1,622,002
of 26,017,215 outputs
Outputs from Genome Biology
#1,320
of 4,513 outputs
Outputs of similar age
#17,509
of 326,441 outputs
Outputs of similar age from Genome Biology
#23
of 97 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
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 has gotten more attention than average, scoring higher than 70% 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 326,441 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 93% of its contemporaries.
We're also able to compare this research output to 97 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.