Evolving Boolean Networks for Biological Control: State Space Targeting in Scale Free Boolean Networks

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Abstract

Gene regulatory networks are the complex dynamical structures that orchestrate the activities of biological cells. Inappropriate dynamical behaviours, caused by mutations or environmental perturbations, can lead to disease. Control interventions, for example in the form of therapeutic drugs, can lead to recovery from disease. In this paper, we consider how Boolean networks can be used to control gene regulatory networks, focusing on the problem of state space targeting in scale-free Boolean networks, an abstract yet realistic model of biological gene regulatory networks. Our results suggest that Boolean networks can be optimised to carry out useful control, and that the approach is relatively scalable. We also take an initial look at the trade-off between the efficacy and efficiency of control, showing that many target networks can be controlled via a relatively small degree of coupling, giving hope that Boolean network controllers could one day be implemented in vivo.
Original languageEnglish
Title of host publication2016 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)
PublisherIEEE
ISBN (Electronic)9781467394727
DOIs
Publication statusPublished - 2 Jan 2017
Event13th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology 2016 - Empress Hotel Chiang Mai, Chiang Mai, Thailand
Duration: 5 Oct 20167 Oct 2016

Conference

Conference13th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology 2016
CountryThailand
CityChiang Mai
Period5/10/167/10/16

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    Taou, N. S., Corne, D., & Lones, M. A. (2017). Evolving Boolean Networks for Biological Control: State Space Targeting in Scale Free Boolean Networks. In 2016 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) [7758125] IEEE. https://doi.org/10.1109/CIBCB.2016.7758125