DocumentCode :
1136761
Title :
Searching of optimal vaccination schedules
Author :
Pennisi, Marzio Alfio ; Pappalardo, Francesco ; Zhang, Ping ; Motta, Santo
Author_Institution :
Dept. of Math. & Comput. Sci., Univ. of Catania, Catania, Italy
Volume :
28
Issue :
4
fYear :
2009
Firstpage :
67
Lastpage :
72
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.
Keywords :
cancer; genetic algorithms; medical computing; bioinformatics; cancer immunopreventive approach; evolutionary algorithms; genetic algorithms; immunoinformatics; optimal vaccination schedules; optimization; Bioinformatics; Cancer; Evolution (biology); Evolutionary computation; Genetic algorithms; Immune system; Optimal scheduling; Protection; Sequences; Vaccines; Algorithms; Animals; Antigens, Neoplasm; B-Lymphocytes; Cancer Vaccines; Computational Biology; Computer Simulation; Humans; Immunization Schedule; Mice; Models, Genetic; Models, Immunological; Neoplasms;
fLanguage :
English
Journal_Title :
Engineering in Medicine and Biology Magazine, IEEE
Publisher :
ieee
ISSN :
0739-5175
Type :
jour
DOI :
10.1109/MEMB.2009.932919
Filename :
5165227
Link To Document :
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