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NBZIMM: negative binomial and zero-inflated mixed models, with application to microbiome/metagenomics data analysis

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 (84th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

blogs
1 blog
twitter
10 X users

Citations

dimensions_citation
53 Dimensions

Readers on

mendeley
82 Mendeley
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Title
NBZIMM: negative binomial and zero-inflated mixed models, with application to microbiome/metagenomics data analysis
Published in
BMC Bioinformatics, October 2020
DOI 10.1186/s12859-020-03803-z
Pubmed ID
Authors

Xinyan Zhang, Nengjun Yi

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 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 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 82 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 16%
Student > Ph. D. Student 11 13%
Student > Bachelor 8 10%
Student > Doctoral Student 6 7%
Student > Master 6 7%
Other 8 10%
Unknown 30 37%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 24%
Biochemistry, Genetics and Molecular Biology 6 7%
Environmental Science 6 7%
Medicine and Dentistry 3 4%
Immunology and Microbiology 2 2%
Other 13 16%
Unknown 32 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 20 May 2021.
All research outputs
#2,516,091
of 23,550,886 outputs
Outputs from BMC Bioinformatics
#761
of 7,413 outputs
Outputs of similar age
#66,705
of 422,187 outputs
Outputs of similar age from BMC Bioinformatics
#22
of 182 outputs
Altmetric has tracked 23,550,886 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,413 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 89% 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 422,187 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 84% of its contemporaries.
We're also able to compare this research output to 182 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.