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Phylotastic! Making tree-of-life knowledge accessible, reusable and convenient

Overview of attention for article published in BMC Bioinformatics, May 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 (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

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41 X users

Citations

dimensions_citation
38 Dimensions

Readers on

mendeley
147 Mendeley
citeulike
5 CiteULike
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Title
Phylotastic! Making tree-of-life knowledge accessible, reusable and convenient
Published in
BMC Bioinformatics, May 2013
DOI 10.1186/1471-2105-14-158
Pubmed ID
Authors

Arlin Stoltzfus, Hilmar Lapp, Naim Matasci, Helena Deus, Brian Sidlauskas, Christian M Zmasek, Gaurav Vaidya, Enrico Pontelli, Karen Cranston, Rutger Vos, Campbell O Webb, Luke J Harmon, Megan Pirrung, Brian O'Meara, Matthew W Pennell, Siavash Mirarab, Michael S Rosenberg, James P Balhoff, Holly M Bik, Tracy A Heath, Peter E Midford, Joseph W Brown, Emily Jane McTavish, Jeet Sukumaran, Mark Westneat, Michael E Alfaro, Aaron Steele, Greg Jordan

Abstract

Scientists rarely reuse expert knowledge of phylogeny, in spite of years of effort to assemble a great "Tree of Life" (ToL). A notable exception involves the use of Phylomatic, which provides tools to generate custom phylogenies from a large, pre-computed, expert phylogeny of plant taxa. This suggests great potential for a more generalized system that, starting with a query consisting of a list of any known species, would rectify non-standard names, identify expert phylogenies containing the implicated taxa, prune away unneeded parts, and supply branch lengths and annotations, resulting in a custom phylogeny suited to the user's needs. Such a system could become a sustainable community resource if implemented as a distributed system of loosely coupled parts that interact through clearly defined interfaces.

X Demographics

X Demographics

The data shown below were collected from the profiles of 41 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 147 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 15 10%
Brazil 3 2%
Chile 2 1%
Netherlands 1 <1%
Germany 1 <1%
Cuba 1 <1%
Sweden 1 <1%
France 1 <1%
Belgium 1 <1%
Other 3 2%
Unknown 118 80%

Demographic breakdown

Readers by professional status Count As %
Researcher 45 31%
Student > Ph. D. Student 26 18%
Student > Master 13 9%
Professor > Associate Professor 12 8%
Student > Bachelor 12 8%
Other 30 20%
Unknown 9 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 74 50%
Computer Science 20 14%
Environmental Science 11 7%
Biochemistry, Genetics and Molecular Biology 7 5%
Engineering 7 5%
Other 17 12%
Unknown 11 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 23. 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 14 June 2013.
All research outputs
#1,672,983
of 25,587,485 outputs
Outputs from BMC Bioinformatics
#273
of 7,722 outputs
Outputs of similar age
#13,402
of 205,429 outputs
Outputs of similar age from BMC Bioinformatics
#5
of 122 outputs
Altmetric has tracked 25,587,485 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,722 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. 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 205,429 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 122 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 96% of its contemporaries.