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A Methodology for Evaluating the Extensibility of Boolean Networks’ Structure and Function

Rémi Segretain 1, 1 Sergiu Ivanov 2, 2 Laurent Trilling 1, 1 Nicolas Glade 1, 1 
1 TIMC-IMAG-BCM - Biologie Computationnelle et Mathématique
TIMC-IMAG - Techniques de l'Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications Grenoble - UMR 5525
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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Submitted on : Wednesday, September 7, 2022 - 9:13:42 PM
Last modification on : Tuesday, October 18, 2022 - 4:31:12 AM


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Rémi Segretain, Sergiu Ivanov, Laurent Trilling, Nicolas Glade. A Methodology for Evaluating the Extensibility of Boolean Networks’ Structure and Function. 9th International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2020), Dec 2020, Madrid, Spain. pp.372-385, ⟨10.1007/978-3-030-65351-4_30⟩. ⟨hal-03168800⟩



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