Living systems are structurally complex, heterogeneous, and by definition out of thermodynamic equilibrium. In condensed matter physics, the complex behavior of many-particle systems has been very successfully analyzed with the concepts of statistical physics. The strength of a statistical approach is the capability to efficiently describe the collective behavior of large systems with many interacting degrees of freedom. In recent years, non-equilibrium soft-matter systems - short: active matter -, especially as found in biology, has rapidly moved into the focus of interest. A prominent example are the materials cells are made from. Understanding how a living cell functions or an organism develops requires a statistical description that goes beyond well-established equilibrium statistical physics.
The rapid development of experimental techniques has given unprecedented access to physical properties of molecules, macromolecular aggregates, cells and tissues. Against this background it is timely to ask questions beyond the molecular level of organization in soft and biological matter and to pursue an integrative approach to understand collective non-equilibrium physical phenomena on the microscopic to the mesoscopic or even macroscopic level by applying a broad range of experimental, numerical and theoretical tools.
The collaborative research center CRC 937 aims at a quantitative understanding of the physical mechanisms at work when soft and biological matter self-organizes into complex structures to perform dynamic functions such as cell division, cell locomotion or tissue development. With this goal in mind, we plan to analyze the ways, in which macromolecules and cells interact physically, exert forces, respond viscoelastically, move each other, and self-organize into complex functional patterns on all length scales, ranging from polymers, lipid membranes over cells to tissues. We combine physics, chemistry, biology and medicine, as well as theory, modeling and experiment and employ a two-pronged approach, studying simplified model systems, on the one hand, and whole organisms and tissues on the other hand.