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GraphML specializations to codify ancestral recombinant graphs

Overview of attention for article published in Frontiers in Genetics, January 2013
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Title
GraphML specializations to codify ancestral recombinant graphs
Published in
Frontiers in Genetics, January 2013
DOI 10.3389/fgene.2013.00146
Pubmed ID
Authors

James R. McGill, Elizabeth A. Walkup, Mary K. Kuhner

Abstract

Software which simulates, infers, or analyzes ancestral recombination graphs (ARGs) faces the problem of communicating them. Existing formats omit information either about the location of recombinations along the chromosome or the position of recombinations relative to the branching topology. We present a specialization of GraphML, an XML-based standard for mathematical graphs, for communication of ARGs. The GraphML <node> type is specialized to contain the node type, time, recombination location, and name. The GraphML <edge> type is specialized to contain the ancestral material passed along that edge. This approach, which we call ArgML, retains all information in the original ARG. Due to its use of established formats ArgML can be parsed, checked and displayed by existing software.

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X Demographics

X Demographics

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.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 9%
Unknown 10 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 36%
Student > Ph. D. Student 2 18%
Other 1 9%
Student > Master 1 9%
Student > Postgraduate 1 9%
Other 0 0%
Unknown 2 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 55%
Biochemistry, Genetics and Molecular Biology 2 18%
Mathematics 1 9%
Engineering 1 9%
Unknown 1 9%
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 06 February 2014.
All research outputs
#14,756,074
of 22,715,151 outputs
Outputs from Frontiers in Genetics
#4,445
of 11,756 outputs
Outputs of similar age
#175,324
of 280,748 outputs
Outputs of similar age from Frontiers in Genetics
#176
of 319 outputs
Altmetric has tracked 22,715,151 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,756 research outputs from this source. They receive a mean Attention Score of 3.7. This one has gotten more attention than average, scoring higher than 54% 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 280,748 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 319 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.