Automated reverse engineering of metabolic pathways from observed data using genetic programming

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

@InCollection{koza:2001:FSB,
  author =       "John R. Koza and William Mydlowec and Guido Lanza and 
                 Jessen Yu and Martin A. Keane",
  title =        "Automated reverse engineering of metabolic pathways
                 from observed data using genetic programming",
  booktitle =    "Foundations of Systems Biology",
  publisher =    "MIT Press",
  year =         "2001",
  editor =       "Hiroaki Kitano",
  pages =        "95--117",
  address =      "Cambridge, MA",
  email =        "john@johnkoza.com",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.genetic-programming.com/jkpdf/kitanochaptericsb2000.pdf",
  size =         "23 pages",
  abstract =     "Recent work has demonstrated that genetic programming
                 is capable of automatically creating complex networks
                 (e.g., analog electrical circuits, controllers) whose
                 behaviour is modelled by linear and non-linear
                 continuous-time differential equations and whose
                 behaviour matches prespecified output values. The
                 concentrations of substances participating in networks
                 of chemical reactions are modelled by non-linear
                 continuous-time differential equations. This chapter
                 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 substances and automatically creates
                 both the topology of the network of chemical reactions
                 and the rates of each reaction of a network such that
                 the behaviour of the automatically created network
                 matches the observed time-domain data. Specifically,
                 genetic programming automatically created a metabolic
                 pathway involving four chemical reactions that consume
                 glycerol and fatty acid as input, use ATP as a
                 cofactor, and produce diacyl-glycerol as the final
                 product. The metabolic pathway was created from 270
                 data points. The automatically created metabolic
                 pathway contain three key topological features,
                 including an internal feedback loop, a bifurcation
                 point where one substance is distributed to two
                 different reactions, and an accumulation point where
                 one substance is accumulated from two sources. The
                 topology and sizing of the entire metabolic pathway was
                 automatically created using only the time-domain
                 concentration values of diacyl-glycerol (the final
                 product).",
}

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

Citations