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X Demographics
Mendeley readers
Attention Score in Context
| Title |
An integrative variant analysis suite for whole exome next-generation sequencing data
|
|---|---|
| Published in |
BMC Bioinformatics, January 2012
|
| DOI | 10.1186/1471-2105-13-8 |
| Pubmed ID | |
| Authors |
Danny Challis, Jin Yu, Uday S Evani, Andrew R Jackson, Sameer Paithankar, Cristian Coarfa, Aleksandar Milosavljevic, Richard A Gibbs, Fuli Yu |
| Abstract |
Whole exome capture sequencing allows researchers to cost-effectively sequence the coding regions of the genome. Although the exome capture sequencing methods have become routine and well established, there is currently a lack of tools specialized for variant calling in this type of data. |
X Demographics
The data shown below were collected from the profiles of 12 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 | 4 | 33% |
| Spain | 2 | 17% |
| Canada | 2 | 17% |
| Venezuela, Bolivarian Republic of | 1 | 8% |
| Germany | 1 | 8% |
| Unknown | 2 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 8 | 67% |
| Members of the public | 4 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 307 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 13 | 4% |
| Netherlands | 3 | <1% |
| United Kingdom | 3 | <1% |
| India | 3 | <1% |
| Sweden | 2 | <1% |
| Korea, Republic of | 2 | <1% |
| France | 1 | <1% |
| Italy | 1 | <1% |
| Denmark | 1 | <1% |
| Other | 3 | <1% |
| Unknown | 275 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 93 | 30% |
| Student > Ph. D. Student | 74 | 24% |
| Other | 29 | 9% |
| Student > Master | 26 | 8% |
| Professor | 14 | 5% |
| Other | 51 | 17% |
| Unknown | 20 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 141 | 46% |
| Biochemistry, Genetics and Molecular Biology | 60 | 20% |
| Computer Science | 31 | 10% |
| Medicine and Dentistry | 21 | 7% |
| Mathematics | 4 | 1% |
| Other | 20 | 7% |
| Unknown | 30 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 23. 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 12 November 2015.
All research outputs
#1,382,842
of 22,661,413 outputs
Outputs from BMC Bioinformatics
#237
of 7,241 outputs
Outputs of similar age
#10,088
of 243,452 outputs
Outputs of similar age from BMC Bioinformatics
#5
of 85 outputs
Altmetric has tracked 22,661,413 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 7,241 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 96% 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 243,452 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 95% of its contemporaries.
We're also able to compare this research output to 85 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 94% of its contemporaries.