01.01.2023 − 31.12.2024
Boolean networks are used extensively to model biological processes. The associated dynamics are usually defined as directed graphs with the assumption of asynchronicity of updates. Analyses of Boolean dynamics are often restricted to the asymptotic behaviour, and say very little about transient behaviour or modularity of attractors.
We propose to expand the analysis of Boolean dynamics by applying techniques of complex network theory to extend our understanding of transient behaviour and of the structure of cyclic attractors. The identification and interpretation of modules in Boolean models can provide a significant contribution in the understanding of biological processes involved for instance in differentiation or phenotype acquisition, with potential application in the control of cellular and spatial decision-making.