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Transposable element detection from whole genome sequence data

Overview of attention for article published in Mobile DNA, December 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#41 of 365)
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

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25 X users
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2 patents
facebook
1 Facebook page

Citations

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138 Dimensions

Readers on

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405 Mendeley
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Title
Transposable element detection from whole genome sequence data
Published in
Mobile DNA, December 2015
DOI 10.1186/s13100-015-0055-3
Pubmed ID
Authors

Adam D. Ewing

Abstract

The number of software tools available for detecting transposable element insertions from whole genome sequence data has been increasing steadily throughout the last ~5 years. Some of these methods have unique features suiting them for particular use cases, but in general they follow one or more of a common set of approaches. Here, detection and filtering approaches are reviewed in the light of transposable element biology and the current state of whole genome sequencing. We demonstrate that the current state-of-the-art methods still do not produce highly concordant results and provide resources to assist future development in transposable element detection methods.

X Demographics

X Demographics

The data shown below were collected from the profiles of 25 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 405 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 2%
Brazil 4 <1%
France 2 <1%
Norway 1 <1%
Sweden 1 <1%
India 1 <1%
Austria 1 <1%
Canada 1 <1%
United Kingdom 1 <1%
Other 2 <1%
Unknown 384 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 104 26%
Researcher 89 22%
Student > Master 51 13%
Student > Bachelor 35 9%
Student > Doctoral Student 18 4%
Other 60 15%
Unknown 48 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 163 40%
Biochemistry, Genetics and Molecular Biology 130 32%
Computer Science 15 4%
Medicine and Dentistry 11 3%
Immunology and Microbiology 4 <1%
Other 19 5%
Unknown 63 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 14 October 2021.
All research outputs
#2,260,149
of 25,619,480 outputs
Outputs from Mobile DNA
#41
of 365 outputs
Outputs of similar age
#37,207
of 401,060 outputs
Outputs of similar age from Mobile DNA
#2
of 8 outputs
Altmetric has tracked 25,619,480 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 365 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one has done well, scoring higher than 89% 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 401,060 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 90% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.