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Bioinformatics Advance Access originally published online on June 5, 2008
Bioinformatics 2008 24(15):1740-1742; doi:10.1093/bioinformatics/btn260
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Optimal vaccination schedules using simulated annealing

Marzio Pennisi 1, Roberto Catanuto 1, Francesco Pappalardo 1,2,* and Santo Motta 1,2

1Department of Mathematics and Computer Science, University of Catania and 2Faculty of Pharmacy, University of Catania, Catania, Italy

*To whom correspondence should be addressed.


  Abstract

Summary: Since few years the problem of finding optimal solutions for drug or vaccine protocols have been tackled using system biology modeling. These approaches are usually computationally expensive. Our previous experiences in optimizing vaccine or drug protocols using genetic algorithms required the use of a high performance computing infrastructure for a couple of days. In the present article we show that by an appropriate use of a different optimization algorithm, the simulated annealing, we have been able to downsize the computational effort by a factor102. The new algorithm requires computational effort that can be achieved by current generation personal computers.

Availability: Software and additional data can be found at http://www.immunomics.eu/SA/

Contact: francesco{at}dmi.unict.it

Associate Editor: Limsoon Wong

Received on March 31, 2008; revised on June 3, 2008; accepted on June 3, 2008

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