Browsing by Author "Hu, Bo"
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Item How input fluctuations reshape the dynamics of a biological switching system(2012) Hu, Bo; Kessler, David A.; Rappel, Wouter-Jan; Levine, Herbert; National Science Foundation; Center for Theoretical Biological Physics; American Physical SocietyAn important task in quantitative biology is to understand the role of stochasticity in biochemical regulation. Here, as an extension of our recent work [Phys. Rev. Lett. 107, 148101 (2011)], we study how input fluctuations affect the stochastic dynamics of a simple biological switch. In our model, the on transition rate of the switch is directly regulated by a noisy input signal, which is described as a non-negative mean-reverting diffusion process. This continuous process can be a good approximation of the discrete birth-death process and is much more analytically tractable.Within this setup, we apply the Feynman-Kac theorem to investigate the statistical features of the output switching dynamics. Consistent with our previous findings, the input noise is found to effectively suppress the input-dependent transitions.We show analytically that this effect becomes significant when the input signal fluctuates greatly in amplitude and reverts slowly to its mean.Item How input noise limits biochemical sensing in ultrasensitive systems(American Physical Society, 2014) Hu, Bo; Rappel, Wouter-Jan; Levine, Herbert; Center for Theoretical Biological PhysicsMany biological processes are regulated by molecular devices that respond in an ultrasensitive fashion to upstream signals. An important question is whether such ultrasensitivity improves or limits its ability to read out the (noisy) input stimuli. Here, we develop a simple model to study the statistical properties of ultrasensitive signaling systems. We demonstrate that the output sensory noise is always bounded, in contrast to earlier theories using the small noise approximation, which tends to overestimate the impact of noise in ultrasensitive pathways. Our analysis also shows that the apparent sensitivity of the system is ultimately constrained by the input signal-to-noise ratio. Thus, ultrasensitivity can improve the precision of biochemical sensing only to a finite extent. This corresponds to a new limit for ultrasensitive signaling systems, which is strictly tighter than the Berg-Purcell limit.