↓ Skip to main content

BEAST: Bayesian evolutionary analysis by sampling trees

Overview of attention for article published in BMC Ecology and Evolution, November 2007
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

news
4 news outlets
blogs
2 blogs
policy
1 policy source
twitter
1 X user
wikipedia
1 Wikipedia page
q&a
1 Q&A thread

Citations

dimensions_citation
10965 Dimensions

Readers on

mendeley
4024 Mendeley
citeulike
18 CiteULike
connotea
6 Connotea
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
BEAST: Bayesian evolutionary analysis by sampling trees
Published in
BMC Ecology and Evolution, November 2007
DOI 10.1186/1471-2148-7-214
Pubmed ID
Authors

Alexei J Drummond, Andrew Rambaut

Abstract

The evolutionary analysis of molecular sequence variation is a statistical enterprise. This is reflected in the increased use of probabilistic models for phylogenetic inference, multiple sequence alignment, and molecular population genetics. Here we present BEAST: a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree. A large number of popular stochastic models of sequence evolution are provided and tree-based models suitable for both within- and between-species sequence data are implemented.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 4,024 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 74 2%
Brazil 49 1%
Germany 32 <1%
United Kingdom 30 <1%
France 18 <1%
Spain 12 <1%
Canada 10 <1%
Switzerland 9 <1%
Mexico 8 <1%
Other 107 3%
Unknown 3675 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 969 24%
Researcher 789 20%
Student > Master 603 15%
Student > Bachelor 330 8%
Student > Doctoral Student 228 6%
Other 665 17%
Unknown 440 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 2317 58%
Biochemistry, Genetics and Molecular Biology 491 12%
Environmental Science 182 5%
Medicine and Dentistry 80 2%
Computer Science 66 2%
Other 361 9%
Unknown 527 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 56. 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 22 September 2023.
All research outputs
#762,113
of 25,373,627 outputs
Outputs from BMC Ecology and Evolution
#151
of 3,714 outputs
Outputs of similar age
#1,263
of 90,950 outputs
Outputs of similar age from BMC Ecology and Evolution
#1
of 35 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 96th percentile: it's in the top 5% 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 particularly well, scoring higher than 95% 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 90,950 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 98% of its contemporaries.
We're also able to compare this research output to 35 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.