IMAG/MSM WG Multiscale Modeling and Viral Pandemics Zoom

To join the meeting:
https://iu.zoom.us/meeting/register/tZYqd-2srD8tGtCXDem4Cka08rBz5fDW0EQR

Please feel free to forward this invitation to anyone you think would be interested.

Thursday November 14 at 3:00PM (EST)

The schedule for this week consists of one presentation:

Jan Rombouts, EMBL Heidelberg, will discuss: Beyond mechanisms: High-Level Descriptions As Components Of Mathematical Models In Biology.
Biological systems are complex. Their behavior is generated by many interacting units, be it molecules, cells or whole organisms. To understand such systems, mathematical modeling is a crucial tool. Often, we do not know the details of the interaction rules, the regulatory networks or cell signaling dynamics that make up a system. However, we may have knowledge about the effective behavior of some components. For example, we may have a measured response curve that is the result of an unknown chemical reaction network, or we have measured an effective cell-cell interaction strength without knowing what leads to this interaction. In such cases, it is possible to use explicit parametrizations of these components as parts of a larger mathematical model. In this talk, I will discuss two distinct examples where we have used such a modeling approach.

The first example is related to bistable switches in the cell cycle. Transitions in the cell cycle, such as the one from interphase into mitosis, are characterized by fast and irreversible switching and hysteresis. One way to look at the cell cycle is as a chain of bistable switches, corresponding to the transitions between the different phases. A full cell-cycle model that describes the molecular players leading to these different switches quickly becomes unwieldy with lots of unknown parameters. We have proposed an approach to model these bistable switches directly as 'modules' that can be included in a larger model, based on a modification of the classical Hill function. I will explain the method, how we applied it to the cell cycle, and discuss some possible applications in other fields.

In the second part, I will discuss currently ongoing work on spatial pattern formation in embryonic development. Many multicellular pattern-forming systems are driven by cell rearrangements due to cell-cell interactions. If the mechanism of these interactions is unknown, nonlocal advection-diffusion equations can be used to effectively model such systems. These models are partial integro-differential equations, where cell-cell interactions by are described by an interaction kernel. We combine these models with experiments on randomized cell reaggregates from mouse embryos. These cells form spatial patterns starting from well-mixed initial conditions. In particular, I will discuss how we use our theoretical and experimental tools to investigate how domain geometry affects pattern formation, and how this matters for embryonic development.