Analysing the role and dynamics of the double toggle switch pattern in gene regulatory networks
A common theme in network science is the specific properties of scale-free neworks, where the node degree distribution follows a power law. Those networks were shown to emerge from simple aggregation rules (Barabasi et al, 2003), but also to underly critical behaviour in an array of contexts (Larremore et al, 2011) (Fronczak et al, 2006). This is perhaps why scale-free networks were shown to maximise information flows in an array of contexts (Massobrio et al, 2015) (Migliano et al, 2020), and indirectly why they are so prevalent in the natural world (Chialvo et al, 2010) (Friston et al, 2012).
This does not imply, however, that all networks are identical in function and behaviour. All types of scale-free networks present some mesoscopic features that seem to underly functional or architectural specificities (Milo et al, 2002). A basic function of developmental systems such as organisms is for example the ability to retain information through time, or in other words memory. However, the stochasticity of genetic expression rises questions on how gene regulatory networks may retain information through time.
The goal of this study is to assess the ability of the double toggle switch pattern to fulfill this function in gene regulatory networks. Using Herbach et al, 2017's model of genetic expression dynamics, I will build from scratch a model of this pattern, and assess in what conditions it may respond to environmental information and retain it through time. The complete version of my report, from which all figures are extracted, can be found here.