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Impact of quality trimming on the efficiency of reads joining and diversity analysis of Illumina paired-end reads in the context of QIIME1 and QIIME2 microbiome analysis frameworks

Overview of attention for article published in BMC Bioinformatics, November 2019
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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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

blogs
1 blog
twitter
37 X users

Citations

dimensions_citation
58 Dimensions

Readers on

mendeley
127 Mendeley
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Title
Impact of quality trimming on the efficiency of reads joining and diversity analysis of Illumina paired-end reads in the context of QIIME1 and QIIME2 microbiome analysis frameworks
Published in
BMC Bioinformatics, November 2019
DOI 10.1186/s12859-019-3187-5
Pubmed ID
Authors

Attayeb Mohsen, Jonguk Park, Yi-An Chen, Hitoshi Kawashima, Kenji Mizuguchi

X Demographics

X Demographics

The data shown below were collected from the profiles of 37 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 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 127 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 22%
Student > Master 22 17%
Researcher 11 9%
Student > Bachelor 10 8%
Other 4 3%
Other 11 9%
Unknown 41 32%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 23%
Biochemistry, Genetics and Molecular Biology 25 20%
Environmental Science 9 7%
Immunology and Microbiology 5 4%
Nursing and Health Professions 3 2%
Other 16 13%
Unknown 40 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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 May 2020.
All research outputs
#1,384,727
of 25,378,799 outputs
Outputs from BMC Bioinformatics
#172
of 7,681 outputs
Outputs of similar age
#28,995
of 366,848 outputs
Outputs of similar age from BMC Bioinformatics
#4
of 225 outputs
Altmetric has tracked 25,378,799 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,681 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 particularly well, scoring higher than 97% 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 366,848 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 225 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.