Stochastic dynamics and topology of biological networks within and between cells (360G-Wellcome-102408_Z_13_Z)

The aim of my project is to combine two lines of inquiry from the Newman Group: i) the effect of topology of gene networks on cellular robustness, and ii) the stochastic dynamics of chains of interactions linking biological states. The overlap between these two themes is a rich, untapped area concerning the selective pressures on biological networks due to intrinsic and/or extrinsic noise. The mathematical aspects are largely independent of the biological scale, and we intend to use theoretical results from intra-cellular systems to study higher-scale networks, such as those describing states of cellular differentiation. Key goals include: i) assessingthe role of fundamental biological properties, such as robustness, on network topologies, ii) using probability theory and rare event statistics to understand non-trivial and counter-intuitive aspects of network dynamics, and iii) uncovering the design principles that allow networks to filter stochasticsignals to produce deterministic outcomes. Our investigations will be coupled to experimental data, such as gene networks, and cell differentiation pathwaysto maximise potential impact on translational applications to human diseases, in particular cancer.