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Cophenetic metrics for phylogenetic trees, after Sokal and Rohlf

Overview of attention for article published in BMC Bioinformatics, January 2013
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Title
Cophenetic metrics for phylogenetic trees, after Sokal and Rohlf
Published in
BMC Bioinformatics, January 2013
DOI 10.1186/1471-2105-14-3
Pubmed ID
Authors

Gabriel Cardona, Arnau Mir, Francesc Rosselló, Lucía Rotger, David Sánchez

Abstract

Phylogenetic tree comparison metrics are an important tool in the study of evolution, and hence the definition of such metrics is an interesting problem in phylogenetics. In a paper in Taxon fifty years ago, Sokal and Rohlf proposed to measure quantitatively the difference between a pair of phylogenetic trees by first encoding them by means of their half-matrices of cophenetic values, and then comparing these matrices. This idea has been used several times since then to define dissimilarity measures between phylogenetic trees but, to our knowledge, no proper metric on weighted phylogenetic trees with nested taxa based on this idea has been formally defined and studied yet. Actually, the cophenetic values of pairs of different taxa alone are not enough to single out phylogenetic trees with weighted arcs or nested taxa.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 8%
United Kingdom 1 3%
Portugal 1 3%
Unknown 33 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 29%
Researcher 7 18%
Student > Postgraduate 3 8%
Student > Bachelor 2 5%
Student > Doctoral Student 2 5%
Other 8 21%
Unknown 5 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 29%
Computer Science 9 24%
Mathematics 5 13%
Biochemistry, Genetics and Molecular Biology 5 13%
Engineering 1 3%
Other 0 0%
Unknown 7 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 31 May 2013.
All research outputs
#16,048,159
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#5,493
of 7,454 outputs
Outputs of similar age
#189,293
of 290,299 outputs
Outputs of similar age from BMC Bioinformatics
#95
of 137 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,454 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
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 290,299 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 137 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.