The Computational Science Lab, led by Peter Sloot, tries to understand how information is processed in natural settings through the study of a large variety of dynamic multi-scale complex systems with a focus on – but not limited to – biomedicine.
We study this 'natural information processing' in complex systems by computational modelling and simulation. An example is the spreading of the HIV virus: many processes on a large range of spatiotemporal scales play a role, from the molecular scale (e.g. the details of the entry of the virus into a cell) to the organism level (the sequence of events leading from an initial infection to the development of AIDS, and medication to keep the infection under control), and even to the population level (the actual spreading of the virus).
We rely on a variety of modelling approaches (such as Agent Based models, Cellular Automata, Dynamic Complex Networks, particle methods, and models based on differential equations), on multiscale modelling methods that capture the transmission and transformation of information up – and down the scales, on formal methods (theories of natural information processing) and on Problem Solving Environments (workflows, visualisation, multiscale coupling libraries and e-science infrastructures for distributed multiscale computing).