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Launching genomics into the cloud: deployment of Mercury, a next generation sequence analysis pipeline

Overview of attention for article published in BMC Bioinformatics, January 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

twitter
24 tweeters
patent
1 patent
facebook
4 Facebook pages

Citations

dimensions_citation
163 Dimensions

Readers on

mendeley
198 Mendeley
citeulike
6 CiteULike
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Title
Launching genomics into the cloud: deployment of Mercury, a next generation sequence analysis pipeline
Published in
BMC Bioinformatics, January 2014
DOI 10.1186/1471-2105-15-30
Pubmed ID
Authors

Jeffrey G Reid, Andrew Carroll, Narayanan Veeraraghavan, Mahmoud Dahdouli, Andreas Sundquist, Adam English, Matthew Bainbridge, Simon White, William Salerno, Christian Buhay, Fuli Yu, Donna Muzny, Richard Daly, Geoff Duyk, Richard A Gibbs, Eric Boerwinkle

Abstract

Massively parallel DNA sequencing generates staggering amounts of data. Decreasing cost, increasing throughput, and improved annotation have expanded the diversity of genomics applications in research and clinical practice. This expanding scale creates analytical challenges: accommodating peak compute demand, coordinating secure access for multiple analysts, and sharing validated tools and results.

Twitter Demographics

The data shown below were collected from the profiles of 24 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 198 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 4%
Germany 3 2%
France 3 2%
United Kingdom 2 1%
Italy 1 <1%
Australia 1 <1%
Brazil 1 <1%
Iceland 1 <1%
Japan 1 <1%
Other 2 1%
Unknown 176 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 55 28%
Student > Ph. D. Student 49 25%
Student > Master 22 11%
Other 12 6%
Professor > Associate Professor 10 5%
Other 39 20%
Unknown 11 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 66 33%
Biochemistry, Genetics and Molecular Biology 40 20%
Computer Science 37 19%
Medicine and Dentistry 16 8%
Engineering 6 3%
Other 17 9%
Unknown 16 8%

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 27 September 2015.
All research outputs
#1,389,826
of 17,961,401 outputs
Outputs from BMC Bioinformatics
#363
of 6,325 outputs
Outputs of similar age
#20,334
of 266,634 outputs
Outputs of similar age from BMC Bioinformatics
#16
of 216 outputs
Altmetric has tracked 17,961,401 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,325 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done particularly well, scoring higher than 94% 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 266,634 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 216 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 93% of its contemporaries.