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Sparse and Compositionally Robust Inference of Microbial Ecological Networks

Overview of attention for article published in PLoS Computational Biology, May 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
policy
2 policy sources
twitter
31 X users
patent
2 patents
googleplus
1 Google+ user
reddit
2 Redditors

Readers on

mendeley
1568 Mendeley
citeulike
3 CiteULike
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Article details
Title
Sparse and Compositionally Robust Inference of Microbial Ecological Networks
Published in
PLoS Computational Biology, May 2015
DOI 10.1371/journal.pcbi.1004226
Pubmed ID
Authors

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Timeline Attention over time Attention Score history
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Activity
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X Demographics

X Demographics

The data shown below were collected from the profiles of 31 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 1,568 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 17 1%
France 3 <1%
United Kingdom 2 <1%
South Africa 1 <1%
Singapore 1 <1%
Sweden 1 <1%
Mexico 1 <1%
Finland 1 <1%
Spain 1 <1%
Other 4 <1%
Unknown 1536 98%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 332 21%
Researcher 293 19%
Student > Master 189 12%
Student > Doctoral Student 96 6%
Student > Bachelor 91 6%
Other 202 13%
Unknown 365 23%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 462 29%
Biochemistry, Genetics and Molecular Biology 208 13%
Environmental Science 114 7%
Immunology and Microbiology 66 4%
Computer Science 56 4%
Other 223 14%
Unknown 439 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 42. 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 24 December 2024.
All research outputs
#1,256,305
of 34,622,316 outputs
Outputs from PLoS Computational Biology
#748
of 10,469 outputs
Outputs of similar age
#12,343
of 307,575 outputs
Outputs of similar age from PLoS Computational Biology
#25
of 168 outputs
Altmetric has tracked 34,622,316 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,469 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.7. This one has done particularly well, scoring higher than 92% 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 307,575 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 95% of its contemporaries.
We're also able to compare this research output to 168 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.