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The use of genome wide association methods to investigate pathogenicity, population structure and serovar in Haemophilus parasuis

Overview of attention for article published in BMC Genomics, December 2014
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Citations

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Title
The use of genome wide association methods to investigate pathogenicity, population structure and serovar in Haemophilus parasuis
Published in
BMC Genomics, December 2014
DOI 10.1186/1471-2164-15-1179
Pubmed ID
Authors

Kate J Howell, Lucy A Weinert, Roy R Chaudhuri, Shi-Lu Luan, Sarah E Peters, Jukka Corander, David Harris, Øystein Angen, Virginia Aragon, Albert Bensaid, Susanna M Williamson, Julian Parkhill, Paul R Langford, Andrew N Rycroft, Brendan W Wren, Matthew T G Holden, Alexander W Tucker, Duncan J Maskell

Abstract

Haemophilus parasuis is the etiologic agent of Glasser's disease in pigs and causes devastating losses to the farming industry. Whilst some hyper-virulent isolates have been described, the relationship between genetics and disease outcome has been only partially established. In particular, there is weak correlation between serovar and disease phenotype. We sequenced the genomes of 212 isolates of H. parasuis and have used this to describe the pan-genome and to correlate this with clinical and carrier status, as well as with serotype.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Russia 1 1%
France 1 1%
Brazil 1 1%
Unknown 72 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 19%
Researcher 14 19%
Student > Ph. D. Student 10 13%
Student > Doctoral Student 7 9%
Student > Bachelor 6 8%
Other 9 12%
Unknown 15 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 31%
Biochemistry, Genetics and Molecular Biology 11 15%
Veterinary Science and Veterinary Medicine 7 9%
Medicine and Dentistry 7 9%
Immunology and Microbiology 5 7%
Other 6 8%
Unknown 16 21%
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 30 December 2014.
All research outputs
#17,286,379
of 25,374,917 outputs
Outputs from BMC Genomics
#7,120
of 11,244 outputs
Outputs of similar age
#220,422
of 359,929 outputs
Outputs of similar age from BMC Genomics
#198
of 313 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 27th percentile – i.e., 27% 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 359,929 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 313 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.