Using detection theory and molecular computation to understand signal processing in living cells

Living cells need to constantly sense their environment, make decision and communicate with other cells. We can try to understand these cellular functions from two angles. We can understand them from the angle of molecular biology and identify all the chemical species, chemical reactions and transport mechanisms that realise these functions. Alternatively, we can understand them from an information processing perspective where cells use networks of chemical reactions (which are also known as molecular circuits) as the substrate to execute algorithms for computation and communication. In this paper, we focus on the cellular signal processing task of discriminating persistent signals from transient ones. We show that we can understand this task by using statistical detection theory, timescale separation and approximate analog molecular computation.