The talk will address some of the key algorithmic and computational challenges associated with the modelling of certain classes of biological networks (e.g. biochemical, signalling). This will involve several research threads that cover a range of theoretical, software and hardware implementation issues. The theoretical modelling developments involve a variety of issues related to the numerical, probabilistic, logical, and symbolic aspects of computation and implementation. A lack of effective tools for modelling and analysing networks has prevented their use in many possible applications. The simulation tools will allow us to develop applications in which millions of randomly generated networks can be simulated and analyzed with great computational efficiency. This efficiency can be obtained by parallelizing the modelling process and address problems that arise from the increasing size of networks and the parallel computing systems that they will require. The problems will include, for example, the unpredictable workload and strong data dependencies characteristic of the modelling of networks; they will require us to investigate a number of related design issues, such as domain decomposition, data access and management, workload balancing, and architecture selection.