Computational models of signalling networks for non-linear control

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@Article{fuente2013computational,
  author =       "Luis A. Fuente and Michael A. Lones and 
                 Alexander P. Turner and Susan Stepney and Leo S. Caves and 
                 Andy M. Tyrrell",
  title =        "Computational models of signalling networks for
                 non-linear control",
  journal =      "Biosystems",
  year =         "2013",
  volume =       "112",
  number =       "2",
  pages =        "122--130",
  note =         "Selected papers from the 9th International Conference
                 on Information Processing in Cells and Tissues",
  keywords =     "genetic algorithms, genetic programming, Cellular
                 signalling, Biochemical networks, Crosstalk,
                 Evolutionary algorithms, Chaos control",
  publisher =    "Elsevier",
  ISSN =         "0303-2647",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0303264713000506",
  DOI =          "doi:10.1016/j.biosystems.2013.03.006",
  abstract =     "Artificial signalling networks (ASNs) are a
                 computational approach inspired by the signalling
                 processes inside cells that decode outside
                 environmental information. Using evolutionary
                 algorithms to induce complex behaviours, we show how
                 chaotic dynamics in a conservative dynamical system can
                 be controlled. Such dynamics are of particular interest
                 as they mimic the inherent complexity of non-linear
                 physical systems in the real world. Considering the
                 main biological interpretations of cellular signalling,
                 in which complex behaviours and robust cellular
                 responses emerge from the interaction of multiple
                 pathways, we introduce two ASN representations: a
                 stand-alone ASN and a coupled ASN. In particular we
                 note how sophisticated cellular communication
                 mechanisms can lead to effective controllers, where
                 complicated problems can be divided into smaller and
                 independent tasks.",
}

Genetic Programming entries for Luis A Fuente Michael A Lones Alexander P Turner Susan Stepney Leo Caves Andrew M Tyrrell

Citations