Systems biology thought experiments in human genetics using artificial life and grammatical evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{white:2004:AL,
  author =       "Bill C. White and Jason H. Moore",
  title =        "Systems biology thought experiments in human genetics
                 using artificial life and grammatical evolution",
  booktitle =    "Artificial Life {XI} Ninth International Conference on
                 the Simulation and Synthesis of Living Systems",
  year =         "2004",
  editor =       "Jordan Pollack and Mark Bedau and Phil Husbands and 
                 Takashi Ikegami and Richard A. Watson",
  pages =        "581--586",
  address =      "Boston, Massachusetts",
  month =        "12-15 " # sep,
  publisher =    "The MIT Press",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution",
  ISBN =         "0-262-66183-7",
  URL =          "http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6278776",
  size =         "6 pages",
  abstract =     "A goal of systems biology and human genetics is to
                 understand how DNA sequence variations impact human
                 health through a hierarchy of biochemical, metabolic,
                 and physiological systems. We present here a
                 proof-of-principle study that demonstrates how
                 artificial life in the form of agent-based simulation
                 can be used to generate hypothetical systems biology
                 models that are consistent with pre-defined genetic
                 models of disease susceptibility. Here, an evolutionary
                 computing strategy called grammatical evolution is used
                 to discover artificial life models. The goal of these
                 studies is to perform thought experiments about the
                 nature of complex biological systems that are
                 consistent with genetic models of disease
                 susceptibility. It is anticipated that the utility of
                 this approach will be the generation of biological
                 hypotheses that can then be tested using experimental
                 systems.",
  notes =        "ALIFE9",
}

Genetic Programming entries for Bill C White Jason H Moore

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