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PHYLOViZ: phylogenetic inference and data visualization for sequence based typing methods

Overview of attention for article published in BMC Bioinformatics, May 2012
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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 (85th percentile)

Mentioned by

twitter
8 tweeters
wikipedia
1 Wikipedia page

Citations

dimensions_citation
363 Dimensions

Readers on

mendeley
255 Mendeley
citeulike
1 CiteULike
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Title
PHYLOViZ: phylogenetic inference and data visualization for sequence based typing methods
Published in
BMC Bioinformatics, May 2012
DOI 10.1186/1471-2105-13-87
Pubmed ID
Authors

Alexandre P Francisco, Cátia Vaz, Pedro T Monteiro, José Melo-Cristino, Mário Ramirez, João A Carriço

Abstract

With the decrease of DNA sequencing costs, sequence-based typing methods are rapidly becoming the gold standard for epidemiological surveillance. These methods provide reproducible and comparable results needed for a global scale bacterial population analysis, while retaining their usefulness for local epidemiological surveys. Online databases that collect the generated allelic profiles and associated epidemiological data are available but this wealth of data remains underused and are frequently poorly annotated since no user-friendly tool exists to analyze and explore it.

Twitter Demographics

The data shown below were collected from the profiles of 8 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 255 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 4 2%
United States 3 1%
United Kingdom 3 1%
France 3 1%
Brazil 2 <1%
Sweden 1 <1%
Germany 1 <1%
New Zealand 1 <1%
Spain 1 <1%
Other 1 <1%
Unknown 235 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 65 25%
Researcher 57 22%
Student > Master 31 12%
Student > Bachelor 21 8%
Student > Doctoral Student 13 5%
Other 39 15%
Unknown 29 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 103 40%
Biochemistry, Genetics and Molecular Biology 41 16%
Immunology and Microbiology 20 8%
Computer Science 16 6%
Veterinary Science and Veterinary Medicine 12 5%
Other 25 10%
Unknown 38 15%

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 05 May 2016.
All research outputs
#2,606,181
of 16,545,042 outputs
Outputs from BMC Bioinformatics
#1,066
of 5,963 outputs
Outputs of similar age
#18,743
of 129,204 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 4 outputs
Altmetric has tracked 16,545,042 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,963 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done well, scoring higher than 82% 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 129,204 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 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them