• DocumentCode
    464307
  • Title

    A Framework for Discrete Modeling of Juxtacrine Signaling Systems

  • Author

    Rozante, Luiz C S ; Gubitoso, Marco D. ; Matioli, Sergio R.

  • Author_Institution
    Dept. of Comput. Sci., Imes Univ.
  • fYear
    2007
  • fDate
    1-5 April 2007
  • Firstpage
    359
  • Lastpage
    366
  • Abstract
    Juxtacrine signaling is intercellular communication, in which the receptor of the signal (typically a protein) as well as the ligand (also typically a protein, responsible for the activation of the receptor) are anchored in the plasma membranes, so that in this type of signaling the activation of the receptor depends on direct contact between the membranes of the cells involved. Juxtacrine signaling is present in many important cellular events of several organisms, especially in the development process. We propose a generic formal model (a modeling framework) for juxtacrine signaling systems that is a class of dynamic discrete systems. It possesses desirable characteristics in a good modeling framework, such as: a) structural similarity with biological models, b) capacity of operating in different scales of time and c) capacity of explicitly treating both the events and molecular elements that occur in the membrane, and those that occur in the intracellular environment and are involved in the juxtacrine signaling process. We implemented this framework and used to develop a new discrete model for the neurogenic network and its participation in neuroblast segregation
  • Keywords
    cellular biophysics; proteins; discrete modeling; dynamic discrete systems; generic formal model; intercellular communication; juxtacrine signaling systems; neuroblast segregation; neurogenic network; plasma membranes; Bioinformatics; Biological system modeling; Biomembranes; Cells (biology); Communication system signaling; Computational intelligence; Mathematical model; Production; Proteins; Signal processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Bioinformatics and Computational Biology, 2007. CIBCB '07. IEEE Symposium on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    1-4244-0710-9
  • Type

    conf

  • DOI
    10.1109/CIBCB.2007.4221245
  • Filename
    4221245