The complex dynamics of biological systems is primarily driven by molecular interactions that underpin the regulatory networks of cells. These networks typically contain positive and negative feedback loops, which are responsible for switch-like and …
Biological systems are adapted to respond quickly to changes in their environment. Signal processing often leads to all-or-none switch-like activation of downstream pathways. Such biological switches are based on molecular interactions that form …
Cells operate in noisy molecular environments via complex regulatory networks. It is possible to understand how molecular counts are related to noise in specific networks, but it is not generally clear how noise relates to network complexity, because …
We consider how to generate chemical reaction networks (CRNs) from functional specifications. We propose a two-stage approach that combines synthesis by satisfiability modulo theories and Markov chain Monte Carlo based optimisation. First, we …
Biological clocks regulate the proper periodicity of several processes at the cellular and organismal level. The cell cycle and circadian rhythm are the best characterized among these but several other biological clocks function in cells at widely …
This chapter demonstrates how linear systems can be used to model biochemical networks. Such models give predictable power that can be used to generate hypotheses, which in turn can be (in)validated experimentally. The advantages of linear systems …
Biological organisms use complex molecular networks to navigate their environment and regulate their internal state. The development of synthetic systems with similar capabilities could lead to applications such as smart therapeutics or fabrication …
The use of mathematical modelling in understanding and dissecting physiological mechanisms in plants has seen many successes. Notably, studies of the component interactions of the Arabidopsis circadian clock have yielded multiple insights into the …