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Mendeley readers
Attention Score in Context
| Title |
Ensembl variation resources
|
|---|---|
| Published in |
BMC Genomics, May 2010
|
| DOI | 10.1186/1471-2164-11-293 |
| Pubmed ID | |
| Authors |
Yuan Chen, Fiona Cunningham, Daniel Rios, William M McLaren, James Smith, Bethan Pritchard, Giulietta M Spudich, Simon Brent, Eugene Kulesha, Pablo Marin-Garcia, Damian Smedley, Ewan Birney, Paul Flicek |
| Abstract |
The maturing field of genomics is rapidly increasing the number of sequenced genomes and producing more information from those previously sequenced. Much of this additional information is variation data derived from sampling multiple individuals of a given species with the goal of discovering new variants and characterising the population frequencies of the variants that are already known. These data have immense value for many studies, including those designed to understand evolution and connect genotype to phenotype. Maximising the utility of the data requires that it be stored in an accessible manner that facilitates the integration of variation data with other genome resources such as gene annotation and comparative genomics. |
Mendeley readers
The data shown below were compiled from readership statistics for 177 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 8 | 5% |
| United States | 5 | 3% |
| Brazil | 5 | 3% |
| France | 2 | 1% |
| Spain | 2 | 1% |
| Germany | 1 | <1% |
| Sweden | 1 | <1% |
| New Zealand | 1 | <1% |
| Norway | 1 | <1% |
| Other | 4 | 2% |
| Unknown | 147 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 50 | 28% |
| Student > Ph. D. Student | 34 | 19% |
| Student > Master | 23 | 13% |
| Student > Bachelor | 18 | 10% |
| Professor > Associate Professor | 9 | 5% |
| Other | 26 | 15% |
| Unknown | 17 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 82 | 46% |
| Biochemistry, Genetics and Molecular Biology | 35 | 20% |
| Computer Science | 16 | 9% |
| Medicine and Dentistry | 12 | 7% |
| Arts and Humanities | 4 | 2% |
| Other | 10 | 6% |
| Unknown | 18 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 20 June 2017.
All research outputs
#2,575,998
of 22,659,164 outputs
Outputs from BMC Genomics
#840
of 10,610 outputs
Outputs of similar age
#9,995
of 94,890 outputs
Outputs of similar age from BMC Genomics
#2
of 45 outputs
Altmetric has tracked 22,659,164 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,610 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 92% 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 94,890 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.