• 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