Our aim: Fundamental research in Theoretical biology and Bioinformatics. Our research is strongly interdisciplinary, both within biology (it ranges from molecular via inter-cellular to eco-evolutionary systems) and within science: we employ and further develop concepts, methods and techniques used/studied in (theoretical) physics, computer science, theoretical chemistry and mathematics, and we collaborate with various experimental groups.
We use the term Bioinformatics in the broad sense: the study of informatic processes in biotic systems. This includes both 'static' bioinformatics (e.g. sequence analysis) and 'dynamic' modeling approaches which emphasize local interactions, information accumulation, transformation and signaling.
The crucial point in modeling biological systems is of course choosing interesting simplifying assumptions which do not 'beg the question' relative to the complexity of the biotic systems studied. New approaches were and are developed and exploited. We pioneered from the 80th onwards the now well established approach of using individuals embedded in space, rather than globally interacting populations as basic variables. Other important inroads to the complexity of biotic systems is to focus on nonlinearity of genotype phenotype mapping, complex boundary conditions, variable interactions structures, and on side effects of e.g. evolution. We develop and use such new approaches alongside the use of more classical approaches like ODE and PDE models: best insights are obtained by a multi-model studies.
Our aim is to understand biotic systems as dynamic information processing systems at many interconnected levels. Our research is knowledge driven; applications are side-effects, but present.