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Patient-Based Transcriptome-Wide Analysis Identify Interferon and Ubiquination Pathways as Potential Predictors of Influenza A Disease Severity

Overview of attention for article published in PLOS ONE, November 2014
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21 Dimensions

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Title
Patient-Based Transcriptome-Wide Analysis Identify Interferon and Ubiquination Pathways as Potential Predictors of Influenza A Disease Severity
Published in
PLOS ONE, November 2014
DOI 10.1371/journal.pone.0111640
Pubmed ID
Authors

Long Truong Hoang, Thomas Tolfvenstam, Eng Eong Ooi, Chiea Chuen Khor, Ahmand Nazri Mohamed Naim, Eliza Xin Pei Ho, Swee Hoe Ong, Heiman F. Wertheim, Annette Fox, Chau Van Vinh Nguyen, Ngoc My Nghiem, Tuan Manh Ha, Anh Thi Ngoc Tran, Paul Tambayah, Raymond Lin, Chariya Sangsajja, Weerawat Manosuthi, Chareon Chuchottaworn, Piamlarp Sansayunh, Tawee Chotpitayasunondh, Piyarat Suntarattiwong, Kulkanya Chokephaibulkit, Pilaipan Puthavathana, Menno D. de Jong, Jeremy Farrar, H. Rogier van Doorn, Martin Lloyd Hibberd

Abstract

The influenza A virus is an RNA virus that is responsible for seasonal epidemics worldwide with up to five million cases of severe illness and 500,000 deaths annually according to the World Health Organization estimates. The factors associated with severe diseases are not well defined, but more severe disease is more often seen among persons aged >65 years, infants, pregnant women, and individuals of any age with underlying health conditions.

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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 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 5%
Netherlands 1 2%
Unknown 38 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 22%
Student > Bachelor 8 20%
Student > Ph. D. Student 6 15%
Student > Doctoral Student 3 7%
Professor > Associate Professor 3 7%
Other 3 7%
Unknown 9 22%
Readers by discipline Count As %
Medicine and Dentistry 11 27%
Agricultural and Biological Sciences 10 24%
Immunology and Microbiology 5 12%
Biochemistry, Genetics and Molecular Biology 3 7%
Veterinary Science and Veterinary Medicine 1 2%
Other 2 5%
Unknown 9 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 20 August 2015.
All research outputs
#15,309,583
of 22,769,322 outputs
Outputs from PLOS ONE
#130,481
of 194,248 outputs
Outputs of similar age
#152,789
of 262,158 outputs
Outputs of similar age from PLOS ONE
#3,051
of 5,109 outputs
Altmetric has tracked 22,769,322 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 194,248 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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 262,158 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5,109 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.