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BarraCUDA - a fast short read sequence aligner using graphics processing units

Overview of attention for article published in BMC Research Notes, January 2012
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1 X user
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1 LinkedIn user

Citations

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114 Dimensions

Readers on

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122 Mendeley
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3 CiteULike
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Title
BarraCUDA - a fast short read sequence aligner using graphics processing units
Published in
BMC Research Notes, January 2012
DOI 10.1186/1756-0500-5-27
Pubmed ID
Authors

Petr Klus, Simon Lam, Dag Lyberg, Ming Sin Cheung, Graham Pullan, Ian McFarlane, Giles SH Yeo, Brian YH Lam

Abstract

With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 122 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 5%
Netherlands 2 2%
United Kingdom 2 2%
Spain 2 2%
Brazil 2 2%
Switzerland 1 <1%
France 1 <1%
Italy 1 <1%
Sweden 1 <1%
Other 5 4%
Unknown 99 81%

Demographic breakdown

Readers by professional status Count As %
Researcher 39 32%
Student > Ph. D. Student 30 25%
Student > Bachelor 10 8%
Student > Master 9 7%
Other 6 5%
Other 16 13%
Unknown 12 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 45 37%
Computer Science 34 28%
Biochemistry, Genetics and Molecular Biology 14 11%
Engineering 4 3%
Medicine and Dentistry 3 2%
Other 6 5%
Unknown 16 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 15 August 2012.
All research outputs
#14,143,189
of 22,663,150 outputs
Outputs from BMC Research Notes
#1,945
of 4,248 outputs
Outputs of similar age
#151,959
of 243,255 outputs
Outputs of similar age from BMC Research Notes
#43
of 79 outputs
Altmetric has tracked 22,663,150 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,248 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 gotten more attention than average, scoring higher than 50% 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 243,255 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 79 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.