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TOPAZ: asymmetric suffix array neighbourhood search for massive protein databases

Overview of attention for article published in BMC Bioinformatics, July 2018
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

twitter
7 X users

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
4 Mendeley
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Title
TOPAZ: asymmetric suffix array neighbourhood search for massive protein databases
Published in
BMC Bioinformatics, July 2018
DOI 10.1186/s12859-018-2290-3
Pubmed ID
Authors

Alan Medlar, Liisa Holm

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Other 1 25%
Student > Postgraduate 1 25%
Student > Master 1 25%
Unknown 1 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 50%
Veterinary Science and Veterinary Medicine 1 25%
Unknown 1 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 09 August 2018.
All research outputs
#7,997,001
of 26,017,215 outputs
Outputs from BMC Bioinformatics
#2,846
of 7,793 outputs
Outputs of similar age
#124,310
of 344,597 outputs
Outputs of similar age from BMC Bioinformatics
#37
of 95 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 7,793 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has gotten more attention than average, scoring higher than 63% 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 344,597 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 63% of its contemporaries.
We're also able to compare this research output to 95 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.