Investigating the use of Boolean networks for the control of gene regulatory networks

Nadia Solime Taou, David Corne, Michael Adam Lones

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)
105 Downloads (Pure)


The behaviour of biological cells emerges from complex patterns of interactions between genes and their products, known as gene regulatory networks (GRN). An important aim of biology is to control the dynamics of GRNs, in order to push a cell towards or away from certain behaviours. This could potentially be done by coupling a synthetic GRN to an existing biological GRN. In this work, we use Boolean networks, a methodology for modelling and simulating GRNs, to investigate the potential for doing this. Our results demonstrate that Boolean networks can be optimised to control other Boolean networks, and that the approach scales well as the target network size increases.
Original languageEnglish
Pages (from-to)147-156
JournalJournal of Computational Science
Early online date22 Apr 2018
Publication statusPublished - May 2018


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