Pappalardo, Francesco, Flower, Darren, Russo, Giulia, Pennisi, Marzio and Motta, Santo (2015). Computational modelling approaches to vaccinology. Pharmacological Research, 92 , pp. 40-45.
Abstract
Excepting the Peripheral and Central Nervous Systems, the Immune System is the most complex of somatic systems in higher animals. This complexity manifests itself at many levels from the molecular to that of the whole organism. Much insight into this confounding complexity can be gained through computational simulation. Such simulations range in application from epitope prediction through to the modelling of vaccination strategies. In this review, we evaluate selectively various key applications relevant to computational vaccinology: these include technique that operates at different scale that is, from molecular to organisms and even to population level.
Publication DOI: | https://doi.org/10.1016/j.phrs.2014.08.006 |
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Divisions: | College of Health & Life Sciences > Aston Pharmacy School College of Health & Life Sciences College of Health & Life Sciences > Chronic and Communicable Conditions |
Additional Information: | NOTICE: this is the author’s version of a work that was accepted for publication in Pharmacological research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Pappalardo, F, Flower, D, Russo, G, Pennisi, M & Motta, S, 'Computational modelling approaches to vaccinology' Pharmacological research, vol 92 (2015) DOI: http://dx.doi.org/10.1016/j.phrs.2014.08.006 |
Uncontrolled Keywords: | computational vaccinology,epitopes,immune system,modelling,simulations,vaccine research,Pharmacology |
Publication ISSN: | 1096-1186 |
Last Modified: | 04 Nov 2024 08:43 |
Date Deposited: | 10 Mar 2015 15:10 |
Full Text Link: | |
Related URLs: |
http://www.scop ... tnerID=8YFLogxK
(Scopus URL) |
PURE Output Type: | Article |
Published Date: | 2015-02 |
Published Online Date: | 2014-09-16 |
Authors: |
Pappalardo, Francesco
Flower, Darren ( 0000-0002-8542-7067) Russo, Giulia Pennisi, Marzio Motta, Santo |