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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, January 2014
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

news
6 news outlets
blogs
2 blogs
twitter
37 X users
facebook
2 Facebook pages

Readers on

mendeley
78 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, January 2014
DOI 10.1186/preaccept-1698056557139770
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 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 profiles of 37 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 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 4%
Germany 2 3%
Sweden 1 1%
Brazil 1 1%
Unknown 71 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 31%
Student > Ph. D. Student 11 14%
Student > Master 8 10%
Other 7 9%
Student > Bachelor 5 6%
Other 16 21%
Unknown 7 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 29%
Biochemistry, Genetics and Molecular Biology 12 15%
Medicine and Dentistry 9 12%
Immunology and Microbiology 8 10%
Nursing and Health Professions 3 4%
Other 12 15%
Unknown 11 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 76. 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 10 August 2015.
All research outputs
#560,814
of 25,394,081 outputs
Outputs from Genome Biology
#333
of 4,470 outputs
Outputs of similar age
#5,593
of 319,334 outputs
Outputs of similar age from Genome Biology
#9
of 116 outputs
Altmetric has tracked 25,394,081 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,470 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 particularly well, scoring higher than 92% 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 319,334 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 98% of its contemporaries.
We're also able to compare this research output to 116 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.