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epitopepredict: a tool for integrated MHC binding prediction
A key step in the cellular adaptive immune response is the presentation of antigens to T cells. Computational prediction of T cell epitopes has many applications in vaccine design and immuno-diagnostics. This is the basis of immunoinformatics, which allows in silico screening of peptides before expe...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
GigaScience Press
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9631954/ https://www.ncbi.nlm.nih.gov/pubmed/36824339 http://dx.doi.org/10.46471/gigabyte.13 |
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author | Farrell, Damien |
author_facet | Farrell, Damien |
author_sort | Farrell, Damien |
collection | PubMed |
description | A key step in the cellular adaptive immune response is the presentation of antigens to T cells. Computational prediction of T cell epitopes has many applications in vaccine design and immuno-diagnostics. This is the basis of immunoinformatics, which allows in silico screening of peptides before experiments are performed. With the availability of whole genomes for many microbial species it is now feasible to computationally screen whole proteomes for candidate peptides. epitopepredict is a programmatic framework and command line tool designed to aid this process. It provides access to multiple binding prediction algorithms under a single interface and scales for whole genomes using multiple target MHC alleles. A web interface is provided to assist visualization and filtering of the results. The software is freely available under an open-source license from https://github.com/dmnfarrell/epitopepredict |
format | Online Article Text |
id | pubmed-9631954 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | GigaScience Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-96319542023-02-22 epitopepredict: a tool for integrated MHC binding prediction Farrell, Damien GigaByte Technical Release A key step in the cellular adaptive immune response is the presentation of antigens to T cells. Computational prediction of T cell epitopes has many applications in vaccine design and immuno-diagnostics. This is the basis of immunoinformatics, which allows in silico screening of peptides before experiments are performed. With the availability of whole genomes for many microbial species it is now feasible to computationally screen whole proteomes for candidate peptides. epitopepredict is a programmatic framework and command line tool designed to aid this process. It provides access to multiple binding prediction algorithms under a single interface and scales for whole genomes using multiple target MHC alleles. A web interface is provided to assist visualization and filtering of the results. The software is freely available under an open-source license from https://github.com/dmnfarrell/epitopepredict GigaScience Press 2021-02-24 /pmc/articles/PMC9631954/ /pubmed/36824339 http://dx.doi.org/10.46471/gigabyte.13 Text en © The Author(s) 2021. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Technical Release Farrell, Damien epitopepredict: a tool for integrated MHC binding prediction |
title | epitopepredict: a tool for integrated MHC binding prediction |
title_full | epitopepredict: a tool for integrated MHC binding prediction |
title_fullStr | epitopepredict: a tool for integrated MHC binding prediction |
title_full_unstemmed | epitopepredict: a tool for integrated MHC binding prediction |
title_short | epitopepredict: a tool for integrated MHC binding prediction |
title_sort | epitopepredict: a tool for integrated mhc binding prediction |
topic | Technical Release |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9631954/ https://www.ncbi.nlm.nih.gov/pubmed/36824339 http://dx.doi.org/10.46471/gigabyte.13 |
work_keys_str_mv | AT farrelldamien epitopepredictatoolforintegratedmhcbindingprediction |