Davies, Matthew N, Guan, Pingping, Blythe, Martin J, Salomon, Jesper, Toseland, Christopher P, Hattotuwagama, Channa, Walshe, Valerie, Doytchinova, Irini A, Flower, Darren R (2007) Using databases and data mining in vaccinology. Expert opinion on drug discovery, 2 (1). pp. 19-35. ISSN 1746-0441. (doi:10.1517/17460441.2.1.19) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:47863)
| The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
| Official URL: https://doi.org/10.1517/17460441.2.1.19 |
Abstract
Throughout time functional immunology has accumulated vast amounts of quantitative and qualitative data relevant to the design and discovery of vaccines. Such data includes, but is not limited to, components of the host and pathogen genome (including antigens and virulence factors), T- and B-cell epitopes and other components of the antigen presentation pathway and allergens. In this review the authors discuss a range of databases that archive such data. Built on such information, increasingly sophisticated data mining techniques have developed that create predictive models of utilitarian value. With special reference to epitope data, the authors discuss the strengths and weaknesses of the available techniques and how they can aid computer-aided vaccine design deliver added value for vaccinology.
| Item Type: | Article |
|---|---|
| DOI/Identification number: | 10.1517/17460441.2.1.19 |
| Subjects: | Q Science |
| Divisions: | Divisions > Division of Natural Sciences > Biosciences |
| Depositing User: | Chris Toseland |
| Date Deposited: | 07 Apr 2015 10:53 UTC |
| Last Modified: | 09 Mar 2023 11:33 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/47863 (The current URI for this page, for reference purposes) |
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