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      Boolean network models of cellular regulation: prospects and limitations

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      Journal of The Royal Society Interface

      The Royal Society

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          Abstract

          Computer models are valuable tools towards an understanding of the cell's biochemical regulatory machinery. Possible levels of description of such models range from modelling the underlying biochemical details to top-down approaches, using tools from the theory of complex networks. The latter, coarse-grained approach is taken where regulatory circuits are classified in graph-theoretical terms, with the elements of the regulatory networks being reduced to simply nodes and links, in order to obtain architectural information about the network. Further, considering dynamics on networks at such an abstract level seems rather unlikely to match dynamical regulatory activity of biological cells. Therefore, it came as a surprise when recently examples of discrete dynamical network models based on very simplistic dynamical elements emerged which in fact do match sequences of regulatory patterns of their biological counterparts. Here I will review such discrete dynamical network models, or Boolean networks, of biological regulatory networks. Further, we will take a look at such models extended with stochastic noise, which allow studying the role of network topology in providing robustness against noise. In the end, we will discuss the interesting question of why at all such simple models can describe aspects of biology despite their simplicity. Finally, prospects of Boolean models in exploratory dynamical models for biological circuits and their mutants will be discussed.

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          Author and article information

          Journal
          Journal of The Royal Society Interface
          J. R. Soc. Interface.
          The Royal Society
          1742-5689
          1742-5662
          August 06 2008
          May 28 2008
          August 06 2008
          : 5
          : suppl_1
          Affiliations
          [1 ]Institute for Theoretical Physics, University of Bremen28359 Bremen, Germany
          Article
          10.1098/rsif.2008.0132.focus
          2386560
          18508746
          8ba0deed-8d4d-414e-80df-edc1bc02ac88
          © 2008

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