Reverse Engineering and Automatic Synthesis of Metabolic Pathways from Observed Data Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.2458

@TechReport{koza:2000:0851,
  author =       "John R. Koza and William Mydlowec and Guido Lanza and 
                 Jessen Yu and Martin A. Keane",
  title =        "Reverse Engineering and Automatic Synthesis of
                 Metabolic Pathways from Observed Data Using Genetic
                 Programming",
  institution =  "Stanford Medical Informatics",
  year =         "2000",
  number =       "SMI-2000-0851",
  month =        nov # " 7",
  email =        "koza@stanford.edu,
                 myd@cs.stanford.edu,guidissimo@hotmail.com,
                 jyu@cs.stanford.edu, makeane@ix.netcom.com",
  keywords =     "genetic algorithms, genetic programming, metabolic
                 pathways, chemical reaction networks",
  URL =          "http://smi.stanford.edu/smi-web/reports/SMI-2000-0851.pdf",
  URL =          "http://smi.stanford.edu/smi-web/research/details.jsp?PubId=851",
  URL =          "http://citeseer.ist.psu.edu/525713.html",
  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 continuous-time
                 differential equations (both linear and non-linear) 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. This paper describes how
                 genetic programming automatically created a metabolic
                 pathway involving four chemical reactions that takes in
                 glycerol and fatty acid as input, uses ATP as a
                 cofactor, and produces diacyl-glycerol as its final
                 product. In addition, this paper describes how genetic
                 programming similarly created a metabolic pathway
                 involving three chemical reactions for the synthesis
                 and degradation of ketone bodies. Both automatically
                 created metabolic pathways contain at least one
                 instance of three noteworthy topological features,
                 namely 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.",
  notes =        "See also \cite{koza:2000:ICSB}

                 These slide transparencies were presented at the
                 Computation in Cells workshop on Tuesday April 18, 2000
                 in Hertfordshire, UK and partially at the tutorial on
                 Saturday April 15, 2000 at the Euro-GP-2000 conference
                 in
                 Edinburgh.

                 http://www.genetic-programming.com/jkpdf/cic2000slides.pdf",
  size =         "53 pages",
}

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