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NetMHC specifications

Information


Unique identifier OMICS_17915
Name NetMHC
Interface Web user interface
Restrictions to use None
Input data A peptide sequence.
Input format FASTA
Computer skills Basic
Version 4.0
Stability Stable
Maintained Yes

Documentation


Maintainer


  • person_outline Morten Nielsen

Additional information


Access available upon request.

Information


Unique identifier OMICS_17915
Name NetMHC
Software type Application/Script
Interface Command line interface
Restrictions to use None
Input data A peptide sequence.
Input format FASTA
Operating system Unix/Linux
Computer skills Advanced
Version 4.0
Stability Stable
Maintained Yes

Versioning


No version available

Documentation


Maintainer


  • person_outline Morten Nielsen

Additional information


Access available upon request.

Publication for NetMHC

NetMHC citations

 (181)
library_books

Cell of origin and mutation pattern define three clinically distinct classes of sebaceous carcinoma

2018
Nat Commun
PMCID: 5951856
PMID: 29760388
DOI: 10.1038/s41467-018-04008-y

[…] iding window of nine amino acids around the mutation site was used to identify all possible sequences arising from a mutation. RNA-seq was used where available to identify only expressed neoepitopes. NetMHC 3.4 was used to identify expressed neoepitopes that were capable of being bound by the matched patient human leukocyte antigen (HLA typing). HLA typing was done by aligning sequences from HLA r […]

library_books

A flexible MHC class I multimer loading system for large scale detection of antigen specific T cells

2018
PMCID: 5940271
PMID: 29666167
DOI: 10.1084/jem.20180156

[…] C; Fig. S2, A and B). Considering their high melting temperatures (∼57 and 47°C, respectively; Fig. S1) and dissociation constants (ILKEPVHGV − Kd = 2.5 nM []; ILKEPVHGA − Kd = 1.1 µM, predicted with NetMHC [; ]), ILKEPVHGV and ILKEPVHGA fail as input peptides in the exchange reaction.We continued the search for optimal peptides binding to HLA–A*02:01, allowing efficient temperature-induced exchan […]

library_books

Computational identification, characterization and validation of potential antigenic peptide vaccines from hrHPVs E6 proteins using immunoinformatics and computational systems biology approaches

2018
PLoS One
PMCID: 5929558
PMID: 29715318
DOI: 10.1371/journal.pone.0196484

[…] sing server for the prediction of CTL epitopes. The Proteomic data from all the hrHPVs were screened to predict potential T-CD8+ (MHC class I binding epitopes) epitopes by using algorithms NetCTL and NetMHC [,]. NetCTL accept FASTA sequence as an input that perform different analysis such as prediction of MHC class I binding affinity, TAP transport efficiency and C-terminal Cleavage activity. Conc […]

library_books

Discrimination Between Human Leukocyte Antigen Class I Bound and Co Purified HIV Derived Peptides in Immunopeptidomics Workflows

2018
Front Immunol
PMCID: 5946011
PMID: 29780384
DOI: 10.3389/fimmu.2018.00912

[…] onstrated a similar enrichment of 9-mers (). Given that 721.221 cells are known to express HLA-E, we first predicted whether the 9-mers eluted from CD4.221 cells would potentially bind to HLA-E using NetMHC4.0. Indeed, over one-third of the eluted 9-mers were predicted to bind to HLA-E (data not shown). However, on closer examination of the sequence motif of eluted 9-mers, a preference for proline […]

library_books

The perfect personalized cancer therapy: cancer vaccines against neoantigens

2018
PMCID: 5910567
PMID: 29678194
DOI: 10.1186/s13046-018-0751-1

[…] expression measured by RNA-seq. Finally, the expressed neoantigens are ranked according to different bioinformatic pipelines as described below. The most popular methods to predict binding to MHC are NetMHC-4 and NetMHCpan []. The last step is the delivery of neoantigens in an immunogenic formulation that includes peptides complexed with adjuvants [] or with liposome particles [22]or delivered as […]

library_books

Opportunities and obstacles for deep learning in biology and medicine

2018
PMCID: 5938574
PMID: 29618526
DOI: 10.1098/rsif.2017.0387

[…] onal vector space based on their context relation to other amino acids before making predictions with a CNN. In a comparison of several current methods, Bhattacharya et al. found that the top methods—NetMHC, NetMHCpan, MHCflurry and MHCnuggets—showed comparable performance, but large differences in speed. Convolutional neural networks (in this case, HLA-CNN) showed comparatively poor performance, […]

Citations

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NetMHC institution(s)
Instituto de Investigaciones Biotecnolo´gicas, Universidad Nacional de San Martin, Buenos Aires, Argentina; Center for Biological Sequence Analysis, Technical University of Denmark, Kgs. Lyngby, Denmark
NetMHC funding source(s)
Supported by Federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under Contract No. HHSN272201200010C and from the Agencia Nacional de Promocion Cientifica y Tecnologica, Argentina (PICT-2012-0115).

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