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QMachine: commodity supercomputing in web browsers

Overview of attention for article published in BMC Bioinformatics, June 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 (94th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

blogs
1 blog
twitter
16 X users
facebook
4 Facebook pages
wikipedia
1 Wikipedia page
googleplus
4 Google+ users

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
94 Mendeley
citeulike
2 CiteULike
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Title
QMachine: commodity supercomputing in web browsers
Published in
BMC Bioinformatics, June 2014
DOI 10.1186/1471-2105-15-176
Pubmed ID
Authors

Sean R Wilkinson, Jonas S Almeida

Abstract

Ongoing advancements in cloud computing provide novel opportunities in scientific computing, especially for distributed workflows. Modern web browsers can now be used as high-performance workstations for querying, processing, and visualizing genomics' "Big Data" from sources like The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) without local software installation or configuration. The design of QMachine (QM) was driven by the opportunity to use this pervasive computing model in the context of the Web of Linked Data in Biomedicine.

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
Brazil 2 2%
Germany 1 1%
Sweden 1 1%
Norway 1 1%
Canada 1 1%
United Kingdom 1 1%
Unknown 84 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 22%
Researcher 19 20%
Student > Master 13 14%
Student > Bachelor 12 13%
Professor > Associate Professor 6 6%
Other 11 12%
Unknown 12 13%
Readers by discipline Count As %
Computer Science 34 36%
Agricultural and Biological Sciences 24 26%
Biochemistry, Genetics and Molecular Biology 5 5%
Medicine and Dentistry 4 4%
Engineering 4 4%
Other 9 10%
Unknown 14 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 27. 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 19 August 2016.
All research outputs
#1,322,559
of 24,226,848 outputs
Outputs from BMC Bioinformatics
#169
of 7,512 outputs
Outputs of similar age
#13,291
of 233,342 outputs
Outputs of similar age from BMC Bioinformatics
#7
of 157 outputs
Altmetric has tracked 24,226,848 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,512 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 97% 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 233,342 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 94% of its contemporaries.
We're also able to compare this research output to 157 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 96% of its contemporaries.