A Statistical Approach Reveals Designs for the Most Robust Stochastic Gene Oscillators.

ABSTRACT: The engineering of transcriptional networks presents many challenges due to the inherent uncertainty in the system structure, changing cellular context, and stochasticity in the governing dynamics. One approach to address these problems is to design and build systems that can function across a range of conditions; that is they are robust to uncertainty in their constituent components. Here we examine the parametric robustness landscape of transcriptional oscillators, which underlie many important processes such as circadian rhythms and the cell cycle, plus also serve as a model for the engineering of complex and emergent phenomena. The central questions that we address are: Can we build genetic oscillators that are more robust than those already constructed? Can we make genetic oscillators

SUBMITTER: Woods ML 

PROVIDER: S-EPMC4914944 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature