Abstract: Biological processes are “noisy” and often exhibit large cell-to-cell variability in their operation,
even in genetically identical cellular backgrounds. Probing the dynamics of biological processes in
single cells has allowed us to acquire detailed snapshots of the stochastic processes that establish
such cellular variability, while uncovering a cohort of new challenges and opportunities. How do we
link the stochastic phenomenon to its exact molecular implementation? What are the appropriate
experimental and mathematical frameworks to interpret single cell data? Are interpretations specific
to the system, or are there general biological motifs and control strategies used to attenuate or
exploit noise? And most notably, how do we assess the impact of biological noise in important
cellular processes on the fitness of an organism? In this talk, we expand on these questions using a
variety of examples. Specifically, we adopt and advocate the viewpoint that stochastic behaviors can
be exploited for efficient system identification of biological circuits, while providing a fertile ground
for mathematical and experimental innovation.
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