Stan Marée pioneered the transition from classical pattern formation theories to multi-level modelling of morphogenesis. He has been acknowledged to be the first one ever to model an organism’s full life cycle using integrated modelling approaches, specifically the life cycle of Dictyostelium discoideum. Throughout the years, he has continued to use his unique approach to multi-cellular systems to successfully show that principles of self-organisation, ingrained in well-established subcellular and cellular processes, can generate novel and useful insights on how organisms, across the kingdoms, are able to function. A good example of this approach is the multi-level experimental-modelling cycle that he led, together with Prof. Scheres from Wageningen University, to unravel how stem cells in the Arabidopsis root regulate asymmetric cell divisions that give rise to two new cell identities at the correct position. Through dissecting the underlying molecular circuit which operates in each cell, he found that it presents a highly robust bistable behaviour, due to two positive feedback loops involving the proteins SHR, SCR and the cell-cycle related players RBR and CYCD6;1. The physical location of the asymmetric stem cell division turned out to rely on the interaction of the plant hormone auxin and the protein SHR, its precise dynamics determined by the crossroads of two perpendicular morphogen gradients, which could all be tested and experimentally verified. In another experiment-model interaction he showed how strain rates and phytohormone signalling can explain plant responses to environmental signals, such as in hypernasty. Again, such insights could only be derived by integrating different levels of interaction within a spatial modelling framework.

Through his ample experience in coordinating cross-disciplinary collaborations on diverse biological systems, ranging from Arabidopsis development to lymph node dynamics, Stann was successful in translating specific biological and biomedical problems into well-designed comprehensive mathematical forms, obtaining quantitative answers related to e.g. the estimation of the fitness of viral strains, HIV dynamics, diabetes disease progression and cellular contact times in immunology.

Throughout his work he became used to bridging multiple scales of organisation. In high-resolution single cell models, Stan was able to show how cells can be induced to acquire and maintain polarity and complex shapes. An important conceptual shift of this work was that not only the intracellular biochemistry determined the shape of the cell, but that the shape in turn could cause internal spatiotemporal reorganisation, rendering traditional reductionist approaches futile. On the next level of organisation, Stan integrated the biophysical properties of single cells, their motility and interactions through intercellular adhesion, to study emerging phenomena on the level of multiple cells and tissues. Important findings were that cell shapes and cell shape changes, for example induced by chemotaxis and cell sorting, can have a dramatic effect on tissue dynamics, to the point of inverting the direction of motion of individual cells. In a close collaboration with physicists and experimental biologists Stan then showed that cell adhesion and cortex contractility determine the cell patterning in the Drosophila retina. On yet another scale, organs arise through highly complex interactions between many cells of different types, involving gene regulatory networks, cell motion and tissue level properties. For example, by modelling the realistic 3D dynamics of a lymph node and making fine-detail comparisons with multi-photon microscopy data, we debunked the dogma that T cells are driven by an intrinsic stop-and-go motion. The modelling guided specific experiments that revealed that instead the T cell behaviour is dictated by the lymph node topology. Finally, he found that individual genes can even affect the ecological scale, by causing an eco-evo inevitability of spatio-temporal patterning in vector distribution.