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X Demographics
Mendeley readers
Attention Score in Context
| Title |
An integrative probabilistic model for identification of structural variation in sequencing data
|
|---|---|
| Published in |
Genome Biology, March 2012
|
| DOI | 10.1186/gb-2012-13-3-r22 |
| Pubmed ID | |
| Authors |
Suzanne S Sindi, Selim Önal, Luke C Peng, Hsin-Ta Wu, Benjamin J Raphael |
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 States | 2 | 25% |
| Canada | 1 | 13% |
| France | 1 | 13% |
| Germany | 1 | 13% |
| Venezuela, Bolivarian Republic of | 1 | 13% |
| United Kingdom | 1 | 13% |
| Unknown | 1 | 13% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 50% |
| Scientists | 3 | 38% |
| Science communicators (journalists, bloggers, editors) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 234 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 13 | 6% |
| Netherlands | 2 | <1% |
| France | 2 | <1% |
| Brazil | 2 | <1% |
| Italy | 1 | <1% |
| Korea, Republic of | 1 | <1% |
| Germany | 1 | <1% |
| India | 1 | <1% |
| United Kingdom | 1 | <1% |
| Other | 6 | 3% |
| Unknown | 204 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 70 | 30% |
| Researcher | 65 | 28% |
| Student > Master | 19 | 8% |
| Professor | 17 | 7% |
| Professor > Associate Professor | 12 | 5% |
| Other | 33 | 14% |
| Unknown | 18 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 116 | 50% |
| Biochemistry, Genetics and Molecular Biology | 38 | 16% |
| Computer Science | 34 | 15% |
| Mathematics | 7 | 3% |
| Engineering | 5 | 2% |
| Other | 11 | 5% |
| Unknown | 23 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. 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 11 January 2017.
All research outputs
#2,160,386
of 25,373,627 outputs
Outputs from Genome Biology
#1,807
of 4,467 outputs
Outputs of similar age
#12,417
of 172,510 outputs
Outputs of similar age from Genome Biology
#12
of 39 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has gotten more attention than average, scoring higher than 59% 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 172,510 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 92% of its contemporaries.
We're also able to compare this research output to 39 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 69% of its contemporaries.