Reverse Engineering of Metabolic Pathways from Observed Data Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{koza:2001:PSB,
  author =       "J. R. Koza and W. Mydlowec and G. Lanza and J. Yu and 
                 M. A. Keane",
  title =        "Reverse Engineering of Metabolic Pathways from
                 Observed Data Using Genetic Programming",
  booktitle =    "Pacific Symposium on Biocomputing 6",
  year =         "2001",
  pages =        "434--445",
  address =      "Hawaii",
  month =        "3-7 " # jan,
  publisher =    "World Scientific press",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://helix-web.stanford.edu/psb01/koza.pdf",
  URL =          "http://citeseer.ist.psu.edu/384424.html",
  size =         "12 pages",
  abstract =     "Recent work has demonstrated that genetic programming
                 is capable of automatically creating complex networks
                 (such as analog electrical circuits and controllers)
                 whose behavior is modeled by linear and non-linear
                 continuous-time differential equations and whose
                 behavior matches prespecified output values. The
                 concentrations of substances participating in networks
                 of chemical reactions are also modeled by non-linear
                 continuous-time differential equations. This paper
                 demonstrates that it is possible to automatically
                 create (reverse engineer) a network of chemical
                 reactions from observed time-domain data. Genetic
                 programming starts with observed time-domain
                 concentrations of input substances and automatically
                 creates both the topology of the network of chemical
                 reactions and the rates of each reaction within the
                 network such that the concentration of the final
                 product of the automatically created network matches
                 the observed time-domain data. Specifically, genetic
                 programming automatically created metabolic pathways
                 involved in the phospholipid cycle and the synthesis
                 and degradation of ketone bodies.",
  notes =        "E-CELL, SPICE3, 270 fitness cases, population size
                 100000",
}

Genetic Programming entries for John Koza William J Mydlowec Guido Lanza Jessen Yu Martin A Keane

Citations