• DocumentCode
    55712
  • Title

    Efficient Modeling and Simulation of Bacteria-Based Nanonetworks with BNSim

  • Author

    Guopeng Wei ; Bogdan, Paul ; Marculescu, Radu

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • Volume
    31
  • Issue
    12
  • fYear
    2013
  • fDate
    Dec-13
  • Firstpage
    868
  • Lastpage
    878
  • Abstract
    Bacteria-based networks are formed using native or engineered bacteria that communicate at nano-scale. This definition includes the micro-scale molecular transportation system which uses chemotactic bacteria for targeted cargo delivery, as well as genetic circuits for intercellular interactions like quorum sensing or light communication. To characterize the dynamics of bacterial networks accurately, we introduce BNSim, an open-source, parallel, stochastic, and multiscale modeling platform which integrates various simulation algorithms, together with genetic circuits and chemotactic pathway models in a complex 3D environment. Moreover, we show how this platform can be used to model synthetic bacterial consortia which implement a XOR function and aggregate nearby bacteria using light communication. Consequently, the results demonstrate how BNSim can predict various properties of realistic bacterial networks and provide guidance for their actual wet-lab implementations.
  • Keywords
    biology computing; cell motility; dynamics; genetic algorithms; microorganisms; nanobiotechnology; stochastic processes; BNSim; XOR function; actual wet-lab implementations; aggregate; bacteria-based nanonetwork modeling; bacteria-based nanonetwork simulation; bacterial network dynamics; chemotactic bacteria; chemotactic pathway models; complex 3D environment; engineered bacteria; genetic circuits; intercellular interactions; light communication; microscale molecular transportation system; multiscale modeling platform; native bacteria; open-source modeling platform; parallel modeling platform; quorum sensing; simulation algorithms; stochastic modeling platform; synthetic bacterial consortia; targeted cargo delivery; Adaptation models; Biological system modeling; Chemicals; Mathematical model; Microorganisms; Nanobioscience; Stochastic processes; Nanotechnology; bacteria consortia; bacteria-based nanonetworks; cyber-physical systems; heterogeneous multicellular system; multiscale modeling; stochastic simulation;
  • fLanguage
    English
  • Journal_Title
    Selected Areas in Communications, IEEE Journal on
  • Publisher
    ieee
  • ISSN
    0733-8716
  • Type

    jour

  • DOI
    10.1109/JSAC.2013.SUP2.12130019
  • Filename
    6708567