PT  - JOURNAL ARTICLE
AU  - Eszter Lakatos
AU  - Michael P.H. Stumpf
TI  - Control mechanisms for stochastic biochemical systems via computation of reachable sets
AID  - 10.1101/079723
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 079723
4099  - http://biorxiv.org/content/early/2016/10/07/079723.short
4100  - http://biorxiv.org/content/early/2016/10/07/079723.full
AB  - Controlling the behaviour of cells by rationally guiding molecular processes is an overarching aim of much of synthetic biology. Molecular processes, however, are notoriously noisy and frequently non-linear. We present an approach to studying the impact of control measures on motifs of molecular interactions, that addresses the problems faced in biological systems: stochasticity, parameter uncertainty, and non-linearity. We show that our reachability analysis formalism can describe the potential behaviour of biological (naturally evolved as well as engineered) systems, and provides a set of bounds on their dynamics at the level of population statistics: for example, we can obtain the possible ranges of means and variances of mRNA and protein expression levels, even in the presence of uncertainty about model parameters.