EGAC: A genetic algorithm to compare chemical reaction networks

Stefano Tognazzi, Max Tschaikowski, Mirco Tribastone, Andrea Vandin

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


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 languageEnglish
Title of host publicationGECCO 2017 - Proceedings of the 2017 Genetic and Evolutionary Computation Conference
Number of pages8
PublisherAssociation for Computing Machinery
Publication date1 Jul 2017
ISBN (Electronic)9781450349208
Publication statusPublished - 1 Jul 2017
Externally publishedYes
Event2017 Genetic and Evolutionary Computation Conference - VIENNA HOUSE ANDEL'S BERLIN Landsberger Allee 106, Berlin, Germany
Duration: 15 Jul 201719 Jul 2017


Conference2017 Genetic and Evolutionary Computation Conference
LocationVIENNA HOUSE ANDEL'S BERLIN Landsberger Allee 106
SponsorAssociation for Computing Machinery, Evolv Technologies, Uber AI Labs
Internet address


  • Chemical Reaction Networks
  • Model Comparison
  • Ordinary Differential Equations

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