Title

Searching of optimal vaccination schedules: Application of genetic algorithms to approach the problem in cancer immunoprevention

Date of this Version

2009

Document Type

Journal Article

Publication Details

Interim status: Citation only.

Pennisi, M. A., Pappalardo, F., Zhang, P., & Motta, S. (2009). Searching of optimal vaccination schedules: Application of genetic algorithms to approach the problem in cancer immunoprevention. IEEE Engineering in medicine and biology magazine, 28(4), 67-72.

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2009 HERDC submission. FoR code: 0903

© Copyright 2009 by the Institute of Electrical and Electronics Engineers, Inc. All rights reserved.

Abstract

Genetic algorithms (GAs) are a particular class of evolutionary algorithms that use techniques inspired by evolutionary biology. These are widely used in different areas of bioinformatics. In immunoinformatics, a common optimization problem is the search of optimal vaccination schedules. The problem of defining optimal schedules is particularly acute in cancer immunopreventive approaches, which requires a sequence of vaccine administrations to keep a high level of protective immunity. This paper presents a formalization of the optimization problem and show how a GA search on a model-based approach can be used to deal with the problem.

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This document has been peer reviewed.