Unraveling the dynamics of living systems: what can noisy trajectories teach us?

The non-equilibrium dynamics of living systems manifests over a broad range of scales: from the power strokes of a molecular motor, to cytoplasmic fluctuations and beating flagella, all the way to migrating cells. By observing the dynamics of such systems, we obtain stochastic trajectories. What do these noisy trajectories teach us about the underlying physics of the system?
In the first part, I will discuss how to extract information from steady-state fluctuations in active biological assemblies. Using a simple model, I will argue that the scaling behaviour of non-equilibrium measures can reveal physical properties of systems architecture and the internal driving.
In the second part of this talk, we consider trajectories of whole cells to unravel the features of their dynamics. Specifically, we study the stochastic dynamics of cells migrating across a physical obstacle in a confining 'two-state' micropattern. Using single-cell trajectories, we infer an equation of cell motion that decomposes the dynamics into deterministic and stochastic contributions. This data-driven approach reveals that such confined cells exhibit intricate non-linear dynamics.