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Inference on admixture fractions in a mechanistic model of recurrent admixture

Overview of attention for article published in Theoretical Population Biology, March 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

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Article details
Title
Inference on admixture fractions in a mechanistic model of recurrent admixture
Published in
Theoretical Population Biology, March 2018
DOI 10.1016/j.tpb.2018.03.006
Pubmed ID
Authors
Abstract

Signatures of recent historical admixture are ubiquitous in human populations. We present a mechanistic model of admixture with two source populations, encompassing recurrent admixture periods and study the distribution of admixture fractions for finite but arbitrary genome size. We provide simulation-based methods to estimate the introgression parameters and discuss the implications of reaching stationarity on estimability of parameters when there are recurrent admixture events with different rates.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 3 30%
Student > Master 3 30%
Professor 1 10%
Student > Bachelor 1 10%
Unknown 2 20%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 30%
Agricultural and Biological Sciences 2 20%
Mathematics 1 10%
Computer Science 1 10%
Social Sciences 1 10%
Other 0 0%
Unknown 2 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 30 May 2018.
All research outputs
#5,591,018
of 29,651,435 outputs
Outputs from Theoretical Population Biology
#91
of 703 outputs
Outputs of similar age
#88,638
of 352,170 outputs
Outputs of similar age from Theoretical Population Biology
#1
of 9 outputs
Altmetric has tracked 29,651,435 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 703 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done well, scoring higher than 86% 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 352,170 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them