Applying Intelligent Computing Techniques to Modeling Biological Networks from Expression Data

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@Article{Lee2008111,
  author =       "Wei-Po Lee and Kung-Cheng Yang",
  title =        "Applying Intelligent Computing Techniques to Modeling
                 Biological Networks from Expression Data",
  journal =      "Genomics, Proteomics \& Bioinformatics",
  volume =       "6",
  number =       "2",
  pages =        "111--120",
  year =         "2008",
  ISSN =         "1672-0229",
  DOI =          "doi:10.1016/S1672-0229(08)60026-1",
  URL =          "http://www.sciencedirect.com/science/article/B82XM-4TSTVT9-6/2/3622f6428cf373014593567706357973",
  keywords =     "genetic algorithms, genetic programming, reverse
                 engineering, system modeling, recurrent neural network,
                 expression data",
  abstract =     "Constructing biological networks is one of the most
                 important issues in systems biology. However,
                 constructing a network from data manually takes a
                 considerable large amount of time, therefore an
                 automated procedure is advocated. To automate the
                 procedure of network construction, in this work we use
                 two intelligent computing techniques, genetic
                 programming and neural computation, to infer two kinds
                 of network models that use continuous variables. To
                 verify the presented approaches, experiments have been
                 conducted and the preliminary results show that both
                 approaches can be used to infer networks
                 successfully.",
}

Genetic Programming entries for Wei-Po Lee Kung-Cheng Yang

Citations