Learn More
Synthetic Biology aspires to design, compose and engineer biological systems that implement specified behaviour. When designing such systems, hypothesis testing via computational modelling and simulation is vital in order to reduce the need of costly wet lab experiments. As a case study, we discuss the use of computational modelling and stochastic(More)
Stochastic simulation algorithms (SSAs) are used to trace realistic trajectories of biochemical systems at low species concentrations. As the complexity of modeled biosystems increases, it is important to select the best performing SSA. Numerous improvements to SSAs have been introduced but they each only tend to apply to a certain class of models. This(More)
In the area of systems and synthetic biology, reliable modelling techniques are required to enable hypothesis testing. Our group is developing and applying stochastic methods to simulate multi-scale, multi-compartment biological models (Romero-Campero et al., 2009). We are using these methods in applications such as modelling gene regulatory networks in(More)
  • 1