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Gene co-expression network analysis identifies porcine genes associated with variation in Salmonella shedding

Overview of attention for article published in BMC Genomics, June 2014
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  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

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Title
Gene co-expression network analysis identifies porcine genes associated with variation in Salmonella shedding
Published in
BMC Genomics, June 2014
DOI 10.1186/1471-2164-15-452
Pubmed ID
Authors

Arun Kommadath, Hua Bao, Adriano S Arantes, Graham S Plastow, Christopher K Tuggle, Shawn MD Bearson, Le Luo Guan, Paul Stothard

Abstract

Salmonella enterica serovar Typhimurium is a gram-negative bacterium that can colonise the gut of humans and several species of food producing farm animals to cause enteric or septicaemic salmonellosis. While many studies have looked into the host genetic response to Salmonella infection, relatively few have used correlation of shedding traits with gene expression patterns to identify genes whose variable expression among different individuals may be associated with differences in Salmonella clearance and resistance. Here, we aimed to identify porcine genes and gene co-expression networks that differentiate distinct responses to Salmonella challenge with respect to faecal Salmonella shedding.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
United States 1 1%
India 1 1%
Brazil 1 1%
Unknown 90 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 20%
Researcher 18 19%
Student > Ph. D. Student 14 15%
Student > Postgraduate 7 7%
Student > Bachelor 6 6%
Other 17 18%
Unknown 13 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 38 40%
Biochemistry, Genetics and Molecular Biology 17 18%
Medicine and Dentistry 11 12%
Veterinary Science and Veterinary Medicine 4 4%
Computer Science 4 4%
Other 4 4%
Unknown 16 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 31 January 2015.
All research outputs
#13,916,134
of 22,757,090 outputs
Outputs from BMC Genomics
#5,336
of 10,637 outputs
Outputs of similar age
#116,847
of 228,827 outputs
Outputs of similar age from BMC Genomics
#85
of 209 outputs
Altmetric has tracked 22,757,090 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,637 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 46th percentile – i.e., 46% 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 228,827 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 209 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.