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Compact representation of k-mer de Bruijn graphs for genome read assembly

Overview of attention for article published in BMC Bioinformatics, October 2013
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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 (88th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

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17 X users
q&a
1 Q&A thread

Citations

dimensions_citation
18 Dimensions

Readers on

mendeley
74 Mendeley
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6 CiteULike
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Title
Compact representation of k-mer de Bruijn graphs for genome read assembly
Published in
BMC Bioinformatics, October 2013
DOI 10.1186/1471-2105-14-313
Pubmed ID
Authors

Einar Andreas Rødland

Abstract

Processing of reads from high throughput sequencing is often done in terms of edges in the de Bruijn graph representing all k-mers from the reads. The memory requirements for storing all k-mers in a lookup table can be demanding, even after removal of read errors, but can be alleviated by using a memory efficient data structure.

X Demographics

X Demographics

The data shown below were collected from the profiles of 17 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 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 7%
France 1 1%
Australia 1 1%
Sweden 1 1%
Brazil 1 1%
Russia 1 1%
Iran, Islamic Republic of 1 1%
Unknown 63 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 24%
Student > Ph. D. Student 16 22%
Student > Master 10 14%
Student > Doctoral Student 7 9%
Other 6 8%
Other 14 19%
Unknown 3 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 35%
Computer Science 23 31%
Biochemistry, Genetics and Molecular Biology 9 12%
Engineering 5 7%
Medicine and Dentistry 2 3%
Other 4 5%
Unknown 5 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 04 July 2020.
All research outputs
#2,894,832
of 24,694,993 outputs
Outputs from BMC Bioinformatics
#875
of 7,571 outputs
Outputs of similar age
#26,084
of 218,221 outputs
Outputs of similar age from BMC Bioinformatics
#14
of 117 outputs
Altmetric has tracked 24,694,993 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,571 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 well, scoring higher than 88% 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 218,221 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 88% of its contemporaries.
We're also able to compare this research output to 117 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.