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@INPROCEEDINGS{Koza01reverseengineering,
    author = {John R. Koza and William 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},
    booktitle = {Paci Symposium on Biocomputing , 6},
    year = {2001},
    pages = {434--445},
    publisher = {Kluwer Academic}
}

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Abstract:

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

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