author = {Segretain, R{\'e}mi and Ivanov, Sergiu and Trilling, Laurent and Glade, Nicolas},
title = {Implementation of a Computing Pipeline for Evaluating the Extensibility of Boolean Networks{\textquoteright} Structure and Function},
elocation-id = {2020.10.02.323949},
year = {2020},
doi = {10.1101/2020.10.02.323949},
publisher = {Cold Spring Harbor Laboratory},
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. Biological Regulation, Biological Networks, Sign Boolean Networks, Complexity, Extensibility, Network GrowthCompeting Interest StatementThe authors have declared no competing interest.},
