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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 (94th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

twitter
25 tweeters
wikipedia
1 Wikipedia page

Citations

dimensions_citation
73 Dimensions

Readers on

mendeley
165 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 25 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 165 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%
Spain 2 1%
South Africa 2 1%
Italy 2 1%
Brazil 2 1%
Australia 1 <1%
Sweden 1 <1%
Norway 1 <1%
Other 3 2%
Unknown 140 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 51 31%
Researcher 49 30%
Student > Master 27 16%
Student > Bachelor 10 6%
Student > Postgraduate 5 3%
Other 17 10%
Unknown 6 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 103 62%
Biochemistry, Genetics and Molecular Biology 22 13%
Computer Science 15 9%
Engineering 5 3%
Environmental Science 4 2%
Other 7 4%
Unknown 9 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 09 September 2014.
All research outputs
#704,240
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#189
of 4,576 outputs
Outputs of similar age
#6,822
of 125,555 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 37 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,576 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done particularly well, scoring higher than 96% 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 125,555 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 94% of its contemporaries.
We're also able to compare this research output to 37 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 97% of its contemporaries.