Abstract
Formal interaction networks are well suited for representing complex biological systems and have been used to model signalling pathways, gene regulatory networks, interaction within ecosystems, etc. In this paper, we introduce Sign Boolean Networks (SBNs), which are a uniform variant of Threshold Boolean Networks (TBFs). We continue the study of the complexity of SBNs and build a new framework for evaluating their ability to extend, i.e. the potential to gain new functions by addition of nodes, while also maintaining the original functions. We describe our software implementation of this framework and show some first results. These results seem to confirm the conjecture that networks of moderate complexity are the most able to grow, because they are not too simple, but also not too constrained, like the highly complex ones.
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Acknowledgements
Sergiu Ivanov is partially supported by the Paris region via the project DIM RFSI n\(^\circ \)2018-03 “Modèles informatiques pour la reprogrammation cellulaire”. The authors would also like to thank the IDEX program of the University Grenoble Alpes for its support through the projects COOL: this work is supported by the French National Research Agency in the framework of the Investissements d’Avenir program (ANR-15-IDEX-02). This work is also supported by the Innovation in Strategic Research program of the University Grenoble Alpes. The authors would thanks Ibrahim Cheddadi for fruitful discussions.
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Segretain, R., Ivanov, S., Trilling, L., Glade, N. (2021). A Methodology for Evaluating the Extensibility of Boolean Networks’ Structure and Function. In: Benito, R.M., Cherifi, C., Cherifi, H., Moro, E., Rocha, L.M., Sales-Pardo, M. (eds) Complex Networks & Their Applications IX. COMPLEX NETWORKS 2020 2020. Studies in Computational Intelligence, vol 944. Springer, Cham. https://doi.org/10.1007/978-3-030-65351-4_30
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