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An improved approximate-Bayesian model-choice method for estimating shared evolutionary history

Overview of attention for article published in BMC Ecology and Evolution, July 2014
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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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

blogs
2 blogs
twitter
5 X users
googleplus
1 Google+ user

Citations

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30 Dimensions

Readers on

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61 Mendeley
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Title
An improved approximate-Bayesian model-choice method for estimating shared evolutionary history
Published in
BMC Ecology and Evolution, July 2014
DOI 10.1186/1471-2148-14-150
Pubmed ID
Authors

Jamie R Oaks

Abstract

To understand biological diversification, it is important to account for large-scale processes that affect the evolutionary history of groups of co-distributed populations of organisms. Such events predict temporally clustered divergences times, a pattern that can be estimated using genetic data from co-distributed species. I introduce a new approximate-Bayesian method for comparative phylogeographical model-choice that estimates the temporal distribution of divergences across taxa from multi-locus DNA sequence data. The model is an extension of that implemented in msBayes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 7%
Portugal 1 2%
France 1 2%
Brazil 1 2%
Unknown 54 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 31%
Researcher 14 23%
Student > Master 8 13%
Professor 5 8%
Student > Doctoral Student 4 7%
Other 9 15%
Unknown 2 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 41 67%
Biochemistry, Genetics and Molecular Biology 5 8%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Environmental Science 1 2%
Veterinary Science and Veterinary Medicine 1 2%
Other 4 7%
Unknown 8 13%
Attention Score in Context

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 11 August 2014.
All research outputs
#1,918,424
of 25,373,627 outputs
Outputs from BMC Ecology and Evolution
#467
of 3,714 outputs
Outputs of similar age
#18,777
of 242,252 outputs
Outputs of similar age from BMC Ecology and Evolution
#11
of 65 outputs
Altmetric has tracked 25,373,627 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 3,714 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. This one has done well, scoring higher than 87% 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 242,252 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 92% of its contemporaries.
We're also able to compare this research output to 65 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.