• DocumentCode
    2074669
  • Title

    Fister-Panetta Upper Bound for Cancer Growth. Some Computational Remarks

  • Author

    Bocu, Razvan ; Tabirca, Sabin ; Chen, Yin Jie

  • Author_Institution
    Univ. Coll. Cork, Cork
  • fYear
    2008
  • fDate
    June 29 2008-July 5 2008
  • Firstpage
    17
  • Lastpage
    22
  • Abstract
    Contemporary people live in a society featured by a continuously increasing complexity. As a consequence, interdisciplinary approaches represent a must for every scientist that aims to efficiently manage a certain problem. Cancer evolution and the associated proper medication strategy is an example of such a complex problem that requires an interdisciplinary approach in order to be properly addressed. The first section addresses some basic aspects regarding how cancer research could benefit from the cooperation between mathematics and biology. The second section of the paper discusses about the cancer modelling at a very basic level and describes a drug medication optimization pattern based on the very well-known model of Fister and Panetta, which is modified in order to increase its readability and predictive capacity.
  • Keywords
    cancer; differential equations; drugs; modelling; Fister-Panetta cancer growth upper bound; Fister-Panetta model predictive capacity; Fister-Panetta model readability; biology; cancer evolution; cancer medication strategy; cancer modelling; cancer research; drug medication optimization pattern; mathematics; Biological system modeling; Cancer; Cells (biology); Drugs; Educational institutions; Evolution (biology); Mathematical model; Medical treatment; Predictive models; Upper bound; Fister-Panetta upper bound; cancer modeling; cancer visualization; drug administration optimization pattern;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biocomputation, Bioinformatics, and Biomedical Technologies, 2008. BIOTECHNO '08. International Conference on
  • Conference_Location
    Bucharest
  • Print_ISBN
    978-0-7695-3191-5
  • Electronic_ISBN
    978-0-7695-3191-5
  • Type

    conf

  • DOI
    10.1109/BIOTECHNO.2008.7
  • Filename
    4561128