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Enhanced methods for unbiased deep sequencing of Lassa and Ebola RNA viruses from clinical and biological samples

Overview of attention for article published in Genome Biology, November 2014
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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 (95th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

news
2 news outlets
blogs
1 blog
twitter
1 X user
patent
5 patents

Citations

dimensions_citation
136 Dimensions

Readers on

mendeley
195 Mendeley
citeulike
2 CiteULike
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Title
Enhanced methods for unbiased deep sequencing of Lassa and Ebola RNA viruses from clinical and biological samples
Published in
Genome Biology, November 2014
DOI 10.1186/s13059-014-0519-7
Pubmed ID
Authors

Christian B Matranga, Kristian G Andersen, Sarah Winnicki, Michele Busby, Adrianne D Gladden, Ryan Tewhey, Matthew Stremlau, Aaron Berlin, Stephen K Gire, Eleina England, Lina M Moses, Tarjei S Mikkelsen, Ikponmwonsa Odia, Philomena E Ehiane, Onikepe Folarin, Augustine Goba, S Humarr Kahn, Donald S Grant, Anna Honko, Lisa Hensley, Christian Happi, Robert F Garry, Christine M Malboeuf, Bruce W Birren, Andreas Gnirke, Joshua Z Levin, Pardis C Sabeti

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 195 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
South Africa 2 1%
Germany 1 <1%
United Kingdom 1 <1%
Unknown 188 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 64 33%
Student > Ph. D. Student 35 18%
Student > Master 18 9%
Other 17 9%
Student > Bachelor 12 6%
Other 30 15%
Unknown 19 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 64 33%
Biochemistry, Genetics and Molecular Biology 39 20%
Medicine and Dentistry 20 10%
Immunology and Microbiology 13 7%
Computer Science 6 3%
Other 26 13%
Unknown 27 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 29. 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 04 December 2023.
All research outputs
#1,351,067
of 25,373,627 outputs
Outputs from Genome Biology
#1,057
of 4,467 outputs
Outputs of similar age
#17,635
of 369,879 outputs
Outputs of similar age from Genome Biology
#19
of 98 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done well, scoring higher than 76% 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 369,879 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 95% of its contemporaries.
We're also able to compare this research output to 98 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.