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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A standard variation file format for human genome sequences
|
|---|---|
| Published in |
Genome Biology, August 2010
|
| DOI | 10.1186/gb-2010-11-8-r88 |
| Pubmed ID | |
| Authors |
Martin G Reese, Barry Moore, Colin Batchelor, Fidel Salas, Fiona Cunningham, Gabor T Marth, Lincoln Stein, Paul Flicek, Mark Yandell, Karen Eilbeck |
| Abstract |
Here we describe the Genome Variation Format (GVF) and the 10Gen dataset. GVF, an extension of Generic Feature Format version 3 (GFF3), is a simple tab-delimited format for DNA variant files, which uses Sequence Ontology to describe genome variation data. The 10Gen dataset, ten human genomes in GVF format, is freely available for community analysis from the Sequence Ontology website and from an Amazon elastic block storage (EBS) snapshot for use in Amazon's EC2 cloud computing environment. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 3 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 191 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 18 | 9% |
| Belgium | 4 | 2% |
| United Kingdom | 3 | 2% |
| Germany | 2 | 1% |
| Italy | 2 | 1% |
| Norway | 1 | <1% |
| Kenya | 1 | <1% |
| Brazil | 1 | <1% |
| Sweden | 1 | <1% |
| Other | 9 | 5% |
| Unknown | 149 | 78% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 71 | 37% |
| Student > Ph. D. Student | 45 | 24% |
| Other | 13 | 7% |
| Professor > Associate Professor | 13 | 7% |
| Student > Master | 13 | 7% |
| Other | 26 | 14% |
| Unknown | 10 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 111 | 58% |
| Biochemistry, Genetics and Molecular Biology | 23 | 12% |
| Computer Science | 21 | 11% |
| Medicine and Dentistry | 12 | 6% |
| Neuroscience | 2 | 1% |
| Other | 4 | 2% |
| Unknown | 18 | 9% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 16 August 2020.
All research outputs
#3,313,461
of 25,374,647 outputs
Outputs from Genome Biology
#2,384
of 4,467 outputs
Outputs of similar age
#12,796
of 103,406 outputs
Outputs of similar age from Genome Biology
#12
of 30 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% 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 is in the 46th percentile – i.e., 46% 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 103,406 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 87% of its contemporaries.
We're also able to compare this research output to 30 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 60% of its contemporaries.