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BIOCOM-PIPE: a new user-friendly metabarcoding pipeline for the characterization of microbial diversity from 16S, 18S and 23S rRNA gene amplicons

Overview of attention for article published in BMC Bioinformatics, October 2020
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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 (81st percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

twitter
16 X users

Citations

dimensions_citation
19 Dimensions

Readers on

mendeley
58 Mendeley
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Title
BIOCOM-PIPE: a new user-friendly metabarcoding pipeline for the characterization of microbial diversity from 16S, 18S and 23S rRNA gene amplicons
Published in
BMC Bioinformatics, October 2020
DOI 10.1186/s12859-020-03829-3
Pubmed ID
Authors

Christophe Djemiel, Samuel Dequiedt, Battle Karimi, Aurélien Cottin, Thibault Girier, Yassin El Djoudi, Patrick Wincker, Mélanie Lelièvre, Samuel Mondy, Nicolas Chemidlin Prévost-Bouré, Pierre-Alain Maron, Lionel Ranjard, Sébastien Terrat

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 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 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 58 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 21%
Other 5 9%
Student > Master 5 9%
Student > Bachelor 5 9%
Student > Ph. D. Student 4 7%
Other 11 19%
Unknown 16 28%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 29%
Biochemistry, Genetics and Molecular Biology 10 17%
Environmental Science 6 10%
Computer Science 3 5%
Engineering 2 3%
Other 6 10%
Unknown 14 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 01 December 2020.
All research outputs
#2,942,169
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#1,009
of 7,388 outputs
Outputs of similar age
#76,614
of 421,209 outputs
Outputs of similar age from BMC Bioinformatics
#33
of 186 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,388 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 86% 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 421,209 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 81% of its contemporaries.
We're also able to compare this research output to 186 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.