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Genetically improved BarraCUDA

Overview of attention for article published in BioData Mining, August 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)

Mentioned by

twitter
16 tweeters

Citations

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3 Dimensions

Readers on

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15 Mendeley

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Summary Twitter Dimensions citations
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Title
Genetically improved BarraCUDA
Published in
BioData Mining, August 2017
DOI 10.1186/s13040-017-0149-1
Pubmed ID
28785314
Authors

W. B. Langdon, Brian Yee Hong Lam

Abstract

BarraCUDA is an open source C program which uses the BWA algorithm in parallel with nVidia CUDA to align short next generation DNA sequences against a reference genome. Recently its source code was optimised using "Genetic Improvement". The genetically improved (GI) code is up to three times faster on short paired end reads from The 1000 Genomes Project and 60% more accurate on a short BioPlanet.com GCAT alignment benchmark. GPGPU BarraCUDA running on a single K80 Tesla GPU can align short paired end nextGen sequences up to ten times faster than bwa on a 12 core server. The speed up was such that the GI version was adopted and has been regularly downloaded from SourceForge for more than 12 months.

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Twitter Demographics

The data shown below were collected from the profiles of 16 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 7%
Unknown 14 93%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 27%
Researcher 3 20%
Student > Ph. D. Student 3 20%
Professor > Associate Professor 2 13%
Student > Bachelor 1 7%
Other 1 7%
Unknown 1 7%
Readers by discipline Count As %
Computer Science 4 27%
Biochemistry, Genetics and Molecular Biology 3 20%
Agricultural and Biological Sciences 3 20%
Engineering 2 13%
Chemical Engineering 1 7%
Other 0 0%
Unknown 2 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 14 August 2017.
All research outputs
#2,847,921
of 17,651,001 outputs
Outputs from BioData Mining
#80
of 275 outputs
Outputs of similar age
#58,560
of 278,519 outputs
Outputs of similar age from BioData Mining
#1
of 1 outputs
Altmetric has tracked 17,651,001 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 275 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has gotten more attention than average, scoring higher than 70% 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 278,519 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 78% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them

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