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Prefix-free parsing for building big BWTs

Overview of attention for article published in Algorithms for Molecular Biology, May 2019
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About this Attention Score

  • Among the highest-scoring outputs from this source (#45 of 213)
  • Good Attention Score compared to outputs of the same age (67th percentile)

Mentioned by

twitter
10 tweeters
facebook
1 Facebook page
reddit
1 Redditor

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
14 Mendeley
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Title
Prefix-free parsing for building big BWTs
Published in
Algorithms for Molecular Biology, May 2019
DOI 10.1186/s13015-019-0148-5
Pubmed ID
Authors

Christina Boucher, Travis Gagie, Alan Kuhnle, Ben Langmead, Giovanni Manzini, Taher Mun

Twitter Demographics

The data shown below were collected from the profiles of 10 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 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 36%
Student > Ph. D. Student 3 21%
Student > Bachelor 2 14%
Professor 1 7%
Student > Doctoral Student 1 7%
Other 1 7%
Unknown 1 7%
Readers by discipline Count As %
Computer Science 7 50%
Agricultural and Biological Sciences 3 21%
Unknown 4 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 22 June 2019.
All research outputs
#3,557,923
of 14,158,129 outputs
Outputs from Algorithms for Molecular Biology
#45
of 213 outputs
Outputs of similar age
#83,280
of 259,256 outputs
Outputs of similar age from Algorithms for Molecular Biology
#1
of 1 outputs
Altmetric has tracked 14,158,129 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 213 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done well, scoring higher than 78% 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 259,256 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% 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