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Dimensional Reduction for the General Markov Model on Phylogenetic Trees

Overview of attention for article published in Bulletin of Mathematical Biology, February 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

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Title
Dimensional Reduction for the General Markov Model on Phylogenetic Trees
Published in
Bulletin of Mathematical Biology, February 2017
DOI 10.1007/s11538-017-0249-6
Pubmed ID
Authors

Jeremy G. Sumner

Abstract

We present a method of dimensional reduction for the general Markov model of sequence evolution on a phylogenetic tree. We show that taking certain linear combinations of the associated random variables (site pattern counts) reduces the dimensionality of the model from exponential in the number of extant taxa, to quadratic in the number of taxa, while retaining the ability to statistically identify phylogenetic divergence events. A key feature is the identification of an invariant subspace which depends only bilinearly on the model parameters, in contrast to the usual multi-linear dependence in the full space. We discuss potential applications including the computation of split (edge) weights on phylogenetic trees from observed sequence data.

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Mendeley readers

Mendeley readers

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Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 100%
Readers by discipline Count As %
Unknown 1 100%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 19 March 2017.
All research outputs
#7,518,189
of 22,953,506 outputs
Outputs from Bulletin of Mathematical Biology
#300
of 1,102 outputs
Outputs of similar age
#145,372
of 422,694 outputs
Outputs of similar age from Bulletin of Mathematical Biology
#5
of 23 outputs
Altmetric has tracked 22,953,506 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,102 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 59% 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 422,694 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 54% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.