Computational modelling approaches to vaccinology

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
Divisions: Life & Health Sciences > Pharmacy
Life & Health Sciences
Life & Health 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
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
Published Date: 2015-02
Authors: Pappalardo, Francesco
Flower, Darren ( 0000-0002-8542-7067)
Russo, Giulia
Pennisi, Marzio
Motta, Santo

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