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Probabilistic modeling of the evolution of gene synteny within reconciled phylogenies

Overview of attention for article published in BMC Bioinformatics, October 2015
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Title
Probabilistic modeling of the evolution of gene synteny within reconciled phylogenies
Published in
BMC Bioinformatics, October 2015
DOI 10.1186/1471-2105-16-s14-s5
Pubmed ID
Authors

Magali Semeria, Eric Tannier, Laurent Guéguen

Abstract

Most models of genome evolution concern either genetic sequences, gene content or gene order. They sometimes integrate two of the three levels, but rarely the three of them. Probabilistic models of gene order evolution usually have to assume constant gene content or adopt a presence/absence coding of gene neighborhoods which is blind to complex events modifying gene content. We propose a probabilistic evolutionary model for gene neighborhoods, allowing genes to be inserted, duplicated or lost. It uses reconciled phylogenies, which integrate sequence and gene content evolution. We are then able to optimize parameters such as phylogeny branch lengths, or probabilistic laws depicting the diversity of susceptibility of syntenic regions to rearrangements. We reconstruct a structure for ancestral genomes by optimizing a likelihood, keeping track of all evolutionary events at the level of gene content and gene synteny. Ancestral syntenies are associated with a probability of presence.

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The data shown below were collected from the profiles of 2 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 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 4%
Unknown 25 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 31%
Student > Master 5 19%
Researcher 4 15%
Professor 3 12%
Professor > Associate Professor 2 8%
Other 2 8%
Unknown 2 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 42%
Computer Science 8 31%
Biochemistry, Genetics and Molecular Biology 3 12%
Earth and Planetary Sciences 1 4%
Unknown 3 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 04 May 2016.
All research outputs
#14,718,998
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#4,813
of 7,400 outputs
Outputs of similar age
#144,525
of 276,834 outputs
Outputs of similar age from BMC Bioinformatics
#88
of 142 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,400 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
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