Modelling and Optimisation of a DNA Stack Nano-Device Using Probabilistic Model Checking

Abstract

A DNA stack nano-device is a bio-computing system that can read and write molecular signals based on DNA-DNA hybridisation and strand displacement. In vitro implementation of the DNA stack faces a number of challenges affecting the performance of the system. In this work, we apply probabilistic model checking to analyse and optimise the DNA stack system. We develop a model framework based on continuous-time Markov chains to quantitatively describe the system behaviour. We use the PRISM probabilistic model checker to answer two important questions: 1) What is the minimum required incubation time to store a signal? And 2) How can we maximise the yield of the system? The results suggest that the incubation time can be reduced from 30 minutes to 5-15 minutes depending on the stack operation stage. In addition, the optimised model shows a 40% increase in the target stack yield. project “Synthetic Portabolomics: Leading the way at the crossroads of the Digital and the Bio Economies” (EP/N031962/1). Krasnogor was supported by the Royal Academy of Engineering under the Chairs in Emerging Technologies scheme.