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Bio.Phylo: A unified toolkit for processing, analyzing and visualizing phylogenetic trees in Biopython

Overview of attention for article published in BMC Bioinformatics, August 2012
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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 (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

twitter
24 tweeters
wikipedia
3 Wikipedia pages

Citations

dimensions_citation
95 Dimensions

Readers on

mendeley
190 Mendeley
citeulike
12 CiteULike
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Title
Bio.Phylo: A unified toolkit for processing, analyzing and visualizing phylogenetic trees in Biopython
Published in
BMC Bioinformatics, August 2012
DOI 10.1186/1471-2105-13-209
Pubmed ID
Authors

Eric Talevich, Brandon M Invergo, Peter JA Cock, Brad A Chapman

Abstract

Ongoing innovation in phylogenetics and evolutionary biology has been accompanied by a proliferation of software tools, data formats, analytical techniques and web servers. This brings with it the challenge of integrating phylogenetic and other related biological data found in a wide variety of formats, and underlines the need for reusable software that can read, manipulate and transform this information into the various forms required to build computational pipelines.

Twitter Demographics

The data shown below were collected from the profiles of 24 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 190 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 4%
United Kingdom 4 2%
Brazil 2 1%
Spain 2 1%
Italy 2 1%
South Africa 2 1%
Sweden 1 <1%
France 1 <1%
Netherlands 1 <1%
Other 2 1%
Unknown 166 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 54 28%
Researcher 52 27%
Student > Master 30 16%
Student > Bachelor 16 8%
Student > Postgraduate 7 4%
Other 20 11%
Unknown 11 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 104 55%
Biochemistry, Genetics and Molecular Biology 34 18%
Computer Science 18 9%
Engineering 5 3%
Environmental Science 4 2%
Other 10 5%
Unknown 15 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 23 March 2018.
All research outputs
#1,276,067
of 17,463,360 outputs
Outputs from BMC Bioinformatics
#312
of 6,171 outputs
Outputs of similar age
#8,980
of 138,280 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 7 outputs
Altmetric has tracked 17,463,360 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,171 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done particularly well, scoring higher than 94% 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 138,280 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 93% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them