Noise Control for DNA Computing
Tomislav Plesa, Konstantinos C. Zygalakis, David F. Anderson, Radek, Erban

TL;DR
This paper introduces a noise-control algorithm for biochemical networks that modifies reaction structures to manage stochastic effects while preserving deterministic behavior, enabling advanced control of noise-induced phenomena.
Contribution
The paper develops a novel algorithm that structurally modifies reaction networks to control intrinsic noise without altering deterministic dynamics, bridging the gap between deterministic and stochastic design.
Findings
Algorithm successfully introduces controllable state-dependent noise.
Redesigns enable noise-induced multistability in production-decay systems.
Controls stochastic switching and induces noise-driven oscillations.
Abstract
Synthetic biology is a growing interdisciplinary field, with far-reaching applications, which aims to design biochemical systems that behave in a desired manner. With the advancement of strand-displacement DNA computing, a large class of abstract biochemical networks may be physically realized using DNA molecules. Methods for systematic design of the abstract systems with prescribed behaviors have been predominantly developed at the (less-detailed) deterministic level. However, stochastic effects, neglected at the deterministic level, are increasingly found to play an important role in biochemistry. In such circumstances, methods for controlling the intrinsic noise in the system are necessary for a successful network design at the (more-detailed) stochastic level. To bridge the gap, the noise-control algorithm for designing biochemical networks is developed in this paper. The algorithm…
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Taxonomy
TopicsGene Regulatory Network Analysis · Advanced biosensing and bioanalysis techniques · DNA and Biological Computing
