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Mendeley readers
Attention Score in Context
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
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.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
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
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.