Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Evolutionary discovery of DFA size and structure
SAC '96 Proceedings of the 1996 ACM symposium on Applied Computing
ACM Computing Surveys (CSUR)
Petri Net Theory and the Modeling of Systems
Petri Net Theory and the Modeling of Systems
Discrete Event Dynamic Systems
Reverse HillclimbingGenetic Algorithms and the Busy Beaver Problem
Proceedings of the 5th International Conference on Genetic Algorithms
Evolving Turing Machines for Biosequence Recognition and Analysis
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Evolving Petri nets with a genetic algorithm
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Grammatical evolution for the discovery of Petri net models of complex genetic systems
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
A hybrid approach to modeling metabolic systems using a geneticalgorithm and simplex method
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Genetic process mining: an experimental evaluation
Data Mining and Knowledge Discovery
EvoBIO '09 Proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Formal verification to enhance evolution of protocols
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
A Software Tool for the Simulation and Optimization of Dynamic Metabolic Models
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
Expert Systems with Applications: An International Journal
Parameter Estimation Using Metaheuristics in Systems Biology: A Comprehensive Review
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
The evolution of higher-level biochemical reaction models
Genetic Programming and Evolvable Machines
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Given concentrations of metabolites over a sequence of time steps, the metabolic pathway prediction problem seeks a set of reactions and rate constants for them that could yield the concentration-time data. Such metabolic pathways can be modeled with Petri nets: bipartite graphs whose nodes are called places and transitions and in which tokens move from place to place through the transitions. Thus the pathway prediction problem can be addressed by searching a space of Petri nets, and such a search can be undertaken evolutionarily.Here, a genetic algorithm performs such a search. The GA seeks only the net's structure; a hill-climbing step applied as part of evaluation approximates parameters associated with the net's transitions. On one contrived problem instance, the GA sometimes identifies the pathway used to generate the given data, but on a second contrived instance, apparently no harder, it fails. On an instance drawn from real biology---the pathway for phospholipid synthesis---the genetic algorithm identifies a Petri net whose pathway is very similar, but not identical to, the real one. In all three cases, the GA develops Petri nets that represent pathways that closely reproduce the target concentration-time data.