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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The fine-scale architecture of structural variants in 17 mouse genomes
|
|---|---|
| Published in |
Genome Biology, March 2012
|
| DOI | 10.1186/gb-2012-13-3-r18 |
| Pubmed ID | |
| Authors |
Binnaz Yalcin, Kim Wong, Amarjit Bhomra, Martin Goodson, Thomas M Keane, David J Adams, Jonathan Flint |
| Abstract |
Accurate catalogs of structural variants (SVs) in mammalian genomes are necessary to elucidate the potential mechanisms that drive SV formation and to assess their functional impact. Next generation sequencing methods for SV detection are an advance on array-based methods, but are almost exclusively limited to four basic types: deletions, insertions, inversions and copy number gains. |
X Demographics
The data shown below were collected from the profiles of 7 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 | 29% |
| United States | 2 | 29% |
| Malaysia | 1 | 14% |
| Unknown | 2 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 57% |
| Scientists | 2 | 29% |
| Science communicators (journalists, bloggers, editors) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 4% |
| Brazil | 3 | 3% |
| Switzerland | 1 | 1% |
| Australia | 1 | 1% |
| Sweden | 1 | 1% |
| Germany | 1 | 1% |
| Japan | 1 | 1% |
| Spain | 1 | 1% |
| Unknown | 80 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 30 | 32% |
| Student > Ph. D. Student | 26 | 28% |
| Student > Master | 10 | 11% |
| Other | 6 | 6% |
| Professor | 6 | 6% |
| Other | 12 | 13% |
| Unknown | 3 | 3% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 52 | 56% |
| Biochemistry, Genetics and Molecular Biology | 16 | 17% |
| Computer Science | 7 | 8% |
| Medicine and Dentistry | 6 | 6% |
| Mathematics | 2 | 2% |
| Other | 3 | 3% |
| Unknown | 7 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 04 April 2012.
All research outputs
#7,895,727
of 25,371,288 outputs
Outputs from Genome Biology
#3,388
of 4,467 outputs
Outputs of similar age
#51,608
of 171,930 outputs
Outputs of similar age from Genome Biology
#32
of 41 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
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 is in the 24th percentile – i.e., 24% 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 171,930 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 41 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.