TY - JOUR T1 - Control mechanisms for stochastic biochemical systems via computation of reachable sets JF - bioRxiv DO - 10.1101/079723 SP - 079723 AU - Eszter Lakatos AU - Michael P.H. Stumpf Y1 - 2016/01/01 UR - http://biorxiv.org/content/early/2016/10/07/079723.abstract N2 - 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. ER -