## Abstract

Discovering relations between chemical reaction networks (CRNs) is a relevant problem in computational systems biology for model reduction, to explain if a given system can be seen as an abstraction of another one; and for model comparison, useful to establish an evolutionary path from simpler networks to more complex ones. This is also related to foundational issues in computer science regarding program equivalence, in light of the established interpretation of a CRN as a kernel programming language for concurrency. Criteria for deciding iftwo CRNs can be formally related have been recently developed, but these require that a candidate mapping be provided. Automatically finding candidate mappings is very hard in general since the search space essentially consists of all possible partitions of a set. In this paper we tackle this problem by developing a genetic algorithm for a class of CRNs called influence networks, which can be used to model a variety of biological systems including cell-cycle switches and gene networks. An extensive numerical evaluation shows that our approach can successfully establish relations between influence networks from the literature which cannot be found by exact algorithms due to their large computational requirements.

Original language | English |
---|---|

Title of host publication | GECCO 2017 - Proceedings of the 2017 Genetic and Evolutionary Computation Conference |

Number of pages | 8 |

Publisher | Association for Computing Machinery |

Publication date | 1 Jul 2017 |

Pages | 833-840 |

ISBN (Electronic) | 9781450349208 |

DOIs | |

Publication status | Published - 1 Jul 2017 |

Externally published | Yes |

Event | 2017 Genetic and Evolutionary Computation Conference - VIENNA HOUSE ANDEL'S BERLIN Landsberger Allee 106, Berlin, Germany Duration: 15 Jul 2017 → 19 Jul 2017 http://gecco-2017.sigevo.org/index.html/HomePage |

### Conference

Conference | 2017 Genetic and Evolutionary Computation Conference |
---|---|

Location | VIENNA HOUSE ANDEL'S BERLIN Landsberger Allee 106 |

Country | Germany |

City | Berlin |

Period | 15/07/2017 → 19/07/2017 |

Sponsor | Association for Computing Machinery, Evolv Technologies, Uber AI Labs |

Internet address |

## Keywords

- Chemical Reaction Networks
- Model Comparison
- Ordinary Differential Equations