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Integrated assessment of predicted MHC binding and cross-conservation with self reveals patterns of viral camouflage

Overview of attention for article published in BMC Bioinformatics, March 2014
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1 X user

Citations

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Title
Integrated assessment of predicted MHC binding and cross-conservation with self reveals patterns of viral camouflage
Published in
BMC Bioinformatics, March 2014
DOI 10.1186/1471-2105-15-s4-s1
Pubmed ID
Authors

Lu He, Anne S De Groot, Andres H Gutierrez, William D Martin, Lenny Moise, Chris Bailey-Kellogg

Abstract

Immune recognition of foreign proteins by T cells hinges on the formation of a ternary complex sandwiching a constituent peptide of the protein between a major histocompatibility complex (MHC) molecule and a T cell receptor (TCR). Viruses have evolved means of "camouflaging" themselves, avoiding immune recognition by reducing the MHC and/or TCR binding of their constituent peptides. Computer-driven T cell epitope mapping tools have been used to evaluate the degree to which particular viruses have used this means of avoiding immune response, but most such analyses focus on MHC-facing 'agretopes'. Here we set out a new means of evaluating the TCR faces of viral peptides in addition to their agretopes, integrating evaluations of both sides of the ternary complex in a single analysis.

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

Geographical breakdown

Country Count As %
Portugal 1 1%
Ireland 1 1%
India 1 1%
United Kingdom 1 1%
United States 1 1%
Unknown 82 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 25%
Student > Ph. D. Student 14 16%
Student > Master 14 16%
Student > Bachelor 10 11%
Other 5 6%
Other 15 17%
Unknown 7 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 32 37%
Medicine and Dentistry 11 13%
Biochemistry, Genetics and Molecular Biology 8 9%
Immunology and Microbiology 7 8%
Computer Science 4 5%
Other 14 16%
Unknown 11 13%
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 19 March 2015.
All research outputs
#15,296,915
of 22,749,166 outputs
Outputs from BMC Bioinformatics
#5,370
of 7,268 outputs
Outputs of similar age
#131,808
of 223,385 outputs
Outputs of similar age from BMC Bioinformatics
#61
of 95 outputs
Altmetric has tracked 22,749,166 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 7,268 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% 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 223,385 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 95 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.