Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic programming (videotape): the movie
Genetic programming (videotape): the movie
Genetic programming II (videotape): the next generation
Genetic programming II (videotape): the next generation
Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
How to build a Beowulf: a guide to the implementation and application of PC clusters
How to build a Beowulf: a guide to the implementation and application of PC clusters
Advances in genetic programming: volume 3
Advances in genetic programming: volume 3
Quantum computing applications of genetic programming
Advances in genetic programming
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Genetic Programming and Data Structures: Genetic Programming + Data Structures = Automatic Programming!
Genetic Programming III: Darwinian Invention & Problem Solving
Genetic Programming III: Darwinian Invention & Problem Solving
Automatic Creation of Human-Competitive Programs and Controllers by Means of Genetic Programming
Genetic Programming and Evolvable Machines
Proceedings of the First European Workshop on Genetic Programming
EuroGP '98 Proceedings of the First European Workshop on Genetic Programming
Proceedings of the 5th European Conference on Genetic Programming
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
Genetic Programming as a Darwinian Invention Machine
Proceedings of the Second European Workshop on Genetic Programming
Hi-index | 0.00 |
The concentrations of substances participating in networks of chemical reactions are often modeled by non-linear continuous-time differential equations. 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. This chapter demonstrates that it is possible to automatically induce (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 behavior of the automatically created network matches the observed time-domain data. Specifically, genetic programming automatically created a network of 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 network was created from 270 data points. The topology and sizing of the entire network was automatically created using the time-domain concentration values of diacyl-glycerol (the final product). The automatically created network contains 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.