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
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