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Identification of Candidate Vaccine Antigens In Silico
The identification of immunogenic whole-protein antigens is fundamental to the successful discovery of candidate subunit vaccines and their rapid, effective, and efficient transformation into clinically useful, commercially successful vaccine formulations. In the wider context of the experimental di...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120937/ http://dx.doi.org/10.1007/978-1-4614-5070-2_3 |
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author | Flower, Darren R. Davies, Matthew N. Doytchinova, Irini A. |
author_facet | Flower, Darren R. Davies, Matthew N. Doytchinova, Irini A. |
author_sort | Flower, Darren R. |
collection | PubMed |
description | The identification of immunogenic whole-protein antigens is fundamental to the successful discovery of candidate subunit vaccines and their rapid, effective, and efficient transformation into clinically useful, commercially successful vaccine formulations. In the wider context of the experimental discovery of vaccine antigens, with particular reference to reverse vaccinology, this chapter adumbrates the principal computational approaches currently deployed in the hunt for novel antigens: genome-level prediction of antigens, antigen identification through the use of protein sequence alignment-based approaches, antigen detection through the use of subcellular location prediction, and the use of alignment-independent approaches to antigen discovery. Reference is also made to the recent emergence of various expert systems for protein antigen identification. |
format | Online Article Text |
id | pubmed-7120937 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
record_format | MEDLINE/PubMed |
spelling | pubmed-71209372020-04-06 Identification of Candidate Vaccine Antigens In Silico Flower, Darren R. Davies, Matthew N. Doytchinova, Irini A. Immunomic Discovery of Adjuvants and Candidate Subunit Vaccines Article The identification of immunogenic whole-protein antigens is fundamental to the successful discovery of candidate subunit vaccines and their rapid, effective, and efficient transformation into clinically useful, commercially successful vaccine formulations. In the wider context of the experimental discovery of vaccine antigens, with particular reference to reverse vaccinology, this chapter adumbrates the principal computational approaches currently deployed in the hunt for novel antigens: genome-level prediction of antigens, antigen identification through the use of protein sequence alignment-based approaches, antigen detection through the use of subcellular location prediction, and the use of alignment-independent approaches to antigen discovery. Reference is also made to the recent emergence of various expert systems for protein antigen identification. 2012-09-28 /pmc/articles/PMC7120937/ http://dx.doi.org/10.1007/978-1-4614-5070-2_3 Text en © Springer Science+Business Media New York 2013 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Flower, Darren R. Davies, Matthew N. Doytchinova, Irini A. Identification of Candidate Vaccine Antigens In Silico |
title | Identification of Candidate Vaccine Antigens In Silico |
title_full | Identification of Candidate Vaccine Antigens In Silico |
title_fullStr | Identification of Candidate Vaccine Antigens In Silico |
title_full_unstemmed | Identification of Candidate Vaccine Antigens In Silico |
title_short | Identification of Candidate Vaccine Antigens In Silico |
title_sort | identification of candidate vaccine antigens in silico |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120937/ http://dx.doi.org/10.1007/978-1-4614-5070-2_3 |
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