Neutral space analysis of gene regulatory network models of salt stress response in Arabidopsis using evolutionary computation

Boolean networks are popular models to represent gene regulatory networks due to their simplicity and capacity to give an initial idea of the qualitative dynamics of a gene regulatory network represented by the temporal evolution of the protein states. In this paper, we analyze the neutral space of Boolean network models of salt stress response in Arabidopsis through the construction of neutral networks. To infer Boolean networks to build the neutral network, we use an evolution strategy that uses a wildtype network to generate initial candidate solutions. We compare the neutral space results when we consider two different wildtypes. Our results show the effectiveness and usefulness of the evolutionary computation approach for this problem, as well as findings related to how the neutral space is shaped depending of the initial wildtype employed as well as particular characteristics of the evolution strategy used in this work.