↓ Skip to main content

Characterization of phylogenetic networks with NetTest

Overview of attention for article published in BMC Bioinformatics, May 2010
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

blogs
1 blog
wikipedia
1 Wikipedia page

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
57 Mendeley
citeulike
4 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Characterization of phylogenetic networks with NetTest
Published in
BMC Bioinformatics, May 2010
DOI 10.1186/1471-2105-11-268
Pubmed ID
Authors

Miguel Arenas, Mateus Patricio, David Posada, Gabriel Valiente

Abstract

Typical evolutionary events like recombination, hybridization or gene transfer make necessary the use of phylogenetic networks to properly depict the evolution of DNA and protein sequences. Although several theoretical classes have been proposed to characterize these networks, they make stringent assumptions that will likely not be met by the evolutionary process. We have recently shown that the complexity of simulated networks is a function of the population recombination rate, and that at moderate and large recombination rates the resulting networks cannot be categorized. However, we do not know whether these results extend to networks estimated from real data.

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 2 4%
Netherlands 1 2%
France 1 2%
Brazil 1 2%
South Africa 1 2%
United Kingdom 1 2%
Spain 1 2%
Unknown 49 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 35%
Student > Ph. D. Student 14 25%
Student > Master 6 11%
Professor > Associate Professor 5 9%
Other 3 5%
Other 7 12%
Unknown 2 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 35 61%
Biochemistry, Genetics and Molecular Biology 5 9%
Arts and Humanities 4 7%
Computer Science 3 5%
Medicine and Dentistry 2 4%
Other 8 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 25 July 2012.
All research outputs
#1,832,661
of 13,079,031 outputs
Outputs from BMC Bioinformatics
#749
of 4,897 outputs
Outputs of similar age
#21,834
of 147,812 outputs
Outputs of similar age from BMC Bioinformatics
#5
of 21 outputs
Altmetric has tracked 13,079,031 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,897 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 84% 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 147,812 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.