The general objective of his unique approach to Multi-level Modelling of Morphogenesis is to generate direct predictions of development, using models with experimentally determined parameters integrated within multi-scale frameworks, which can be verified experimentally through genetic, molecular and biophysical perturbations. To do so, the Marée Lab has developed an extensive computational environment for cell-based modelling, Excalib, which has central importance to unravel how (sub) cellular processes drive cell shape and topology, in its turn steering development. To validate and challenge the models, he is continuously developing novel image analysis tools, as well as directly linking them to the modelling environment. Moreover, the Marée Lab has developed high-throughput imaging strategies for multi-cellular tissues that are currently for application in biomedical research.

Crossing scales, information processing through excitable media asks questions how even a point mutation in an ion channel can not only change the bursting of a single neuron, but fundamentally modify the collective behaviour of neuronal tissue; it questions how the patterning changes the structure of the organism and the structure of the organism changes its patterning. Combining Extracellular Multi-Electrode Array (MEA) measurements, big data analysis and mechanistic modelling, we aim to to unravel how single point mutations can affect brain functioning.