• DocumentCode
    1159526
  • Title

    Input-State Approach to Boolean Networks

  • Author

    Cheng, Daizhan

  • Author_Institution
    Inst. of Syst. Sci., Chinese Acad. of Sci., Beijing
  • Volume
    20
  • Issue
    3
  • fYear
    2009
  • fDate
    3/1/2009 12:00:00 AM
  • Firstpage
    512
  • Lastpage
    521
  • Abstract
    This paper investigates the structure of Boolean networks via input-state structure. Using the algebraic form proposed by the author, the logic-based input-state dynamics of Boolean networks, called the Boolean control networks, is converted into an algebraic discrete-time dynamic system. Then the structure of cycles of Boolean control systems is obtained as compounded cycles. Using the obtained input-state description, the structure of Boolean networks is investigated, and their attractors are revealed as nested compounded cycles, called rolling gears. This structure explains why small cycles mainly decide the behaviors of cellular networks. Some illustrative examples are presented.
  • Keywords
    Boolean algebra; cellular neural nets; discrete time systems; graph theory; Boolean control networks; algebraic discrete-time dynamic system; cellular networks; logic-based input-state dynamics; rolling gears; Algebraic form; input-state structure; invariant subspace; network transition matrix; Algorithms; Genes; Logic; Neural Networks (Computer); Proteins; Signal Transduction;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/TNN.2008.2011359
  • Filename
    4783102