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EGN: a wizard for construction of gene and genome similarity networks

Overview of attention for article published in BMC Evolutionary Biology, January 2013
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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 (87th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

blogs
1 blog
twitter
3 tweeters
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

dimensions_citation
34 Dimensions

Readers on

mendeley
105 Mendeley
citeulike
3 CiteULike
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Title
EGN: a wizard for construction of gene and genome similarity networks
Published in
BMC Evolutionary Biology, January 2013
DOI 10.1186/1471-2148-13-146
Pubmed ID
Authors

Sébastien Halary, James O McInerney, Philippe Lopez, Eric Bapteste

Abstract

Increasingly, similarity networks are being used for evolutionary analyses of molecular datasets. These networks are very useful, in particular for the analysis of gene sharing, lateral gene transfer and for the detection of distant homologs. Currently, such analyses require some computer programming skills due to the limited availability of user-friendly freely distributed software. Consequently, although appealing, the construction and analyses of these networks remain less familiar to biologists than do phylogenetic approaches.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 2%
Brazil 2 2%
United States 2 2%
Ireland 1 <1%
France 1 <1%
United Kingdom 1 <1%
Canada 1 <1%
New Zealand 1 <1%
Sweden 1 <1%
Other 0 0%
Unknown 93 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 32 30%
Student > Ph. D. Student 30 29%
Student > Doctoral Student 8 8%
Professor > Associate Professor 7 7%
Student > Master 6 6%
Other 16 15%
Unknown 6 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 67 64%
Biochemistry, Genetics and Molecular Biology 9 9%
Computer Science 8 8%
Engineering 3 3%
Immunology and Microbiology 3 3%
Other 9 9%
Unknown 6 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 01 April 2014.
All research outputs
#1,381,225
of 12,373,386 outputs
Outputs from BMC Evolutionary Biology
#535
of 2,341 outputs
Outputs of similar age
#18,618
of 148,105 outputs
Outputs of similar age from BMC Evolutionary Biology
#9
of 17 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,341 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has done well, scoring higher than 77% 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 148,105 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 87% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.