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Synopsis

Persistence despite external perturbations and internal fluctuations is a hallmark of cellular life. The biochemical processes which underly such robustness involve many components whose interactions are stochastic and only partially observed. This makes it difficult to develop reliable models of natural regulatory processes and to engineer molecular control circuits. In this talk I will describe approaches to understand biochemical networks in terms of structural properties which are independent of unknown details. First, I will present a characterization of the stochastic noise properties of 鈥渦niversal biomolecular integral controllers鈥�, which ensure robust adaptation of molecular abundances in arbitrary networks. I will then show how statistical invariants can be used to derive impossibility constraints for incompletely specified systems. In particular, I will describe how broad classes of molecular assembly processes are limited by an efficiency-fluctuation trade-off. Finally, I will discuss 鈥渒inetic uncertainty relations鈥� that arise from constraints on mutual information flow and ongoing work to connect such trade-offs to the entropy production of noise-suppressing control.