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NetMHCIIpan-3.0, a common pan-specific MHC class II prediction method including all three human MHC class II isotypes, HLA-DR, HLA-DP and HLA-DQ

Overview of attention for article published in Immunogenetics, July 2013
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  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

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1 tweeter
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5 patents

Citations

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125 Dimensions

Readers on

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192 Mendeley
Title
NetMHCIIpan-3.0, a common pan-specific MHC class II prediction method including all three human MHC class II isotypes, HLA-DR, HLA-DP and HLA-DQ
Published in
Immunogenetics, July 2013
DOI 10.1007/s00251-013-0720-y
Pubmed ID
Authors

Edita Karosiene, Michael Rasmussen, Thomas Blicher, Ole Lund, Søren Buus, Morten Nielsen

Abstract

Major histocompatibility complex class II (MHCII) molecules play an important role in cell-mediated immunity. They present specific peptides derived from endosomal proteins for recognition by T helper cells. The identification of peptides that bind to MHCII molecules is therefore of great importance for understanding the nature of immune responses and identifying T cell epitopes for the design of new vaccines and immunotherapies. Given the large number of MHC variants, and the costly experimental procedures needed to evaluate individual peptide-MHC interactions, computational predictions have become particularly attractive as first-line methods in epitope discovery. However, only a few so-called pan-specific prediction methods capable of predicting binding to any MHC molecule with known protein sequence are currently available, and all of them are limited to HLA-DR. Here, we present the first pan-specific method capable of predicting peptide binding to any HLA class II molecule with a defined protein sequence. The method employs a strategy common for HLA-DR, HLA-DP and HLA-DQ molecules to define the peptide-binding MHC environment in terms of a pseudo sequence. This strategy allows the inclusion of new molecules even from other species. The method was evaluated in several benchmarks and demonstrates a significant improvement over molecule-specific methods as well as the ability to predict peptide binding of previously uncharacterised MHCII molecules. To the best of our knowledge, the NetMHCIIpan-3.0 method is the first pan-specific predictor covering all HLA class II molecules with known sequences including HLA-DR, HLA-DP, and HLA-DQ. The NetMHCpan-3.0 method is available at http://www.cbs.dtu.dk/services/NetMHCIIpan-3.0 .

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 192 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 2 1%
Argentina 2 1%
Germany 2 1%
United States 2 1%
United Kingdom 2 1%
Denmark 1 <1%
Ireland 1 <1%
Kenya 1 <1%
Korea, Republic of 1 <1%
Other 2 1%
Unknown 176 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 43 22%
Student > Ph. D. Student 41 21%
Student > Bachelor 28 15%
Student > Master 25 13%
Other 13 7%
Other 42 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 69 36%
Biochemistry, Genetics and Molecular Biology 31 16%
Unspecified 21 11%
Immunology and Microbiology 19 10%
Medicine and Dentistry 18 9%
Other 34 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 09 February 2017.
All research outputs
#3,052,586
of 12,216,894 outputs
Outputs from Immunogenetics
#187
of 1,048 outputs
Outputs of similar age
#46,705
of 199,112 outputs
Outputs of similar age from Immunogenetics
#1
of 8 outputs
Altmetric has tracked 12,216,894 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1,048 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done well, scoring higher than 81% 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 199,112 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them