Speaker
Description
Recent advances in synthetic biology have made it possible to deploy chemical reactions that implement computation inside a cell. On the theoretical side, several algorithms have been proposed that optimize for accuracy, computational speed, and resource efficiency. Most of these algorithms, however, rely on two assumptions: (i) the parameters or reaction rate constants are perfectly known, and (ii) the rate constants are insensitive to fluctuating environmental conditions. Neither of these assumptions is realistic in practice, as rate constants are subject to physical, biochemical, and physiological variability, and difficult to measure accurately. We develop a novel repertoire of chemical reactions that perform arithmetic computations, including the operations of addition, rectified subtraction, multiplication, division and $n$th roots -- with the key property that the reaction network modules may contain rate constants that are unknown or environment-dependent. Furthermore, the modules may be used as building blocks to produce arbitrary composite computations while retaining rate-constant independence.
