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Sequencing the genome of the Burmese python (Python molurus bivittatus) as a model for studying extreme adaptations in snakes

Overview of attention for article published in Genome Biology (Online Edition), January 2011
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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 (93rd percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
32 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
47 Dimensions

Readers on

mendeley
157 Mendeley
citeulike
1 CiteULike
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Title
Sequencing the genome of the Burmese python (Python molurus bivittatus) as a model for studying extreme adaptations in snakes
Published in
Genome Biology (Online Edition), January 2011
DOI 10.1186/gb-2011-12-7-406
Pubmed ID
Authors

Todd A Castoe, AP Jason de Koning, Kathryn T Hall, Ken D Yokoyama, Wanjun Gu, Eric N Smith, Cédric Feschotte, Peter Uetz, David A Ray, Jason Dobry, Robert Bogden, Stephen P Mackessy, Anne M Bronikowski, Wesley C Warren, Stephen M Secor, David D Pollock

Abstract

The Consortium for Snake Genomics is in the process of sequencing the genome and creating transcriptomic resources for the Burmese python. Here, we describe how this will be done, what analyses this work will include, and provide a timeline.

Twitter Demographics

The data shown below were collected from the profiles of 32 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 157 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 4 3%
United States 4 3%
United Kingdom 2 1%
Germany 1 <1%
Sweden 1 <1%
Canada 1 <1%
China 1 <1%
Japan 1 <1%
Turkey 1 <1%
Other 1 <1%
Unknown 140 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 36 23%
Student > Ph. D. Student 33 21%
Student > Master 25 16%
Student > Bachelor 13 8%
Professor > Associate Professor 10 6%
Other 32 20%
Unknown 8 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 113 72%
Biochemistry, Genetics and Molecular Biology 21 13%
Environmental Science 3 2%
Earth and Planetary Sciences 2 1%
Computer Science 2 1%
Other 6 4%
Unknown 10 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 16 June 2019.
All research outputs
#1,051,504
of 15,444,557 outputs
Outputs from Genome Biology (Online Edition)
#1,086
of 3,329 outputs
Outputs of similar age
#6,046
of 91,661 outputs
Outputs of similar age from Genome Biology (Online Edition)
#2
of 6 outputs
Altmetric has tracked 15,444,557 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,329 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.1. This one has gotten more attention than average, scoring higher than 67% 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 91,661 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.