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Strainer: Software for analysis of population variation in community genomic datasets

Overview of attention for article published in BMC Bioinformatics, January 2007
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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 (91st percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

blogs
1 blog
twitter
4 tweeters

Citations

dimensions_citation
29 Dimensions

Readers on

mendeley
115 Mendeley
citeulike
9 CiteULike
connotea
1 Connotea
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Title
Strainer: Software for analysis of population variation in community genomic datasets
Published in
BMC Bioinformatics, January 2007
DOI 10.1186/1471-2105-8-398
Pubmed ID
Authors

John M Eppley, Gene W Tyson, Wayne M Getz, Jillian F Banfield

Abstract

Metagenomic analyses of microbial communities that are comprehensive enough to provide multiple samples of most loci in the genomes of the dominant organism types will also reveal patterns of genetic variation within natural populations. New bioinformatic tools will enable visualization and comprehensive analysis of this sequence variation and inference of recent evolutionary and ecological processes.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 115 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 12 10%
Spain 2 2%
Denmark 2 2%
United Kingdom 1 <1%
Brazil 1 <1%
Belgium 1 <1%
Australia 1 <1%
France 1 <1%
Germany 1 <1%
Other 0 0%
Unknown 93 81%

Demographic breakdown

Readers by professional status Count As %
Researcher 33 29%
Student > Ph. D. Student 29 25%
Professor > Associate Professor 18 16%
Student > Doctoral Student 6 5%
Professor 6 5%
Other 19 17%
Unknown 4 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 73 63%
Computer Science 10 9%
Environmental Science 7 6%
Biochemistry, Genetics and Molecular Biology 5 4%
Immunology and Microbiology 4 3%
Other 9 8%
Unknown 7 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 September 2019.
All research outputs
#1,192,197
of 13,968,403 outputs
Outputs from BMC Bioinformatics
#399
of 5,210 outputs
Outputs of similar age
#1,148,048
of 13,243,059 outputs
Outputs of similar age from BMC Bioinformatics
#399
of 5,210 outputs
Altmetric has tracked 13,968,403 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,210 research outputs from this source. They receive a mean Attention Score of 4.9. 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 13,243,059 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 91% of its contemporaries.
We're also able to compare this research output to 5,210 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 92% of its contemporaries.