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Beyond classification: gene-family phylogenies from shotgun metagenomic reads enable accurate community analysis

Overview of attention for article published in BMC Genomics, June 2013
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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 (88th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

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26 X users

Citations

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6 Dimensions

Readers on

mendeley
98 Mendeley
citeulike
4 CiteULike
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Title
Beyond classification: gene-family phylogenies from shotgun metagenomic reads enable accurate community analysis
Published in
BMC Genomics, June 2013
DOI 10.1186/1471-2164-14-419
Pubmed ID
Authors

Samantha J Riesenfeld, Katherine S Pollard

Abstract

Sequence-based phylogenetic trees are a well-established tool for characterizing diversity of both macroorganisms and microorganisms. Phylogenetic methods have recently been applied to shotgun metagenomic data from microbial communities, particularly with the aim of classifying reads. But the accuracy of gene-family phylogenies that characterize evolutionary relationships among short, non-overlapping sequencing reads has not been thoroughly evaluated.

X Demographics

X Demographics

The data shown below were collected from the profiles of 26 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 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 7%
Japan 2 2%
United Kingdom 2 2%
Netherlands 1 1%
France 1 1%
Sweden 1 1%
Canada 1 1%
Germany 1 1%
Estonia 1 1%
Other 3 3%
Unknown 78 80%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 31%
Researcher 24 24%
Student > Master 14 14%
Professor 8 8%
Student > Bachelor 5 5%
Other 9 9%
Unknown 8 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 54 55%
Biochemistry, Genetics and Molecular Biology 7 7%
Computer Science 6 6%
Environmental Science 5 5%
Engineering 4 4%
Other 11 11%
Unknown 11 11%
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 10 August 2014.
All research outputs
#2,827,416
of 25,371,288 outputs
Outputs from BMC Genomics
#852
of 11,244 outputs
Outputs of similar age
#23,824
of 209,393 outputs
Outputs of similar age from BMC Genomics
#26
of 180 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. 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 209,393 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 88% of its contemporaries.
We're also able to compare this research output to 180 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.