• DocumentCode
    2394015
  • Title

    A shooting algorithm for complex immunodominance control problems

  • Author

    Zhao, Xiaopeng ; Yang, Ruoting ; Zhang, Mingjun

  • Author_Institution
    Mech., Aerosp. & Biomed. Eng. Dept., Univ. of Tennessee, Knoxville, TN, USA
  • fYear
    2009
  • fDate
    3-6 Sept. 2009
  • Firstpage
    3897
  • Lastpage
    3900
  • Abstract
    Although T cells are able to recognize a wide variety of target peptides, they are often strongly focused on a few of the peptides and leave the rest of them unattended. This phenomenon of strongly biased immune response is known as immunodominance. Mathematically, an immunodominance problem can be formulated using optimal control principles as a two-point boundary-value problem. The solution of this problem is challenging especially when the control variables are bounded. In this work, we develop a numerical algorithm based on the shooting technique for bounded optimal control problems. The algorithm is applied to a group of immunodominance problems. Numerical simulations reveal that the immune system selects either a broad or a specific strategy of immunodominance based on different optimization goals. The shooting algorithm can also be utilized to solve other complex optimal control problems.
  • Keywords
    biocontrol; biology computing; boundary-value problems; cellular biophysics; molecular biophysics; optimal control; T cells; bounded optimal control problems; immune response; immunodominance control problem; shooting algorithm; target peptides; two-point boundary-value problem; Algorithms; Animals; Computer Simulation; Epitopes; Humans; Immune System; Infection; Models, Biological; Models, Immunological; Models, Theoretical; Monte Carlo Method; Mutation; Peptides; Software; T-Lymphocytes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
  • Conference_Location
    Minneapolis, MN
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-3296-7
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2009.5333566
  • Filename
    5333566