Emergence and control in development and evolution

I am broadly interested in how to make simple models of complex phenomena. In physics, we understand why there is a hierarchy of theories and we can model phenomena at long length scales without necessarily understanding the microscopic physics (https://journals.aps.org/pre/abstract/10.1103/PhysRevE.98.052112). This phenomena is sometimes referred to as emergence. Biology seems more complicated and it is still not yet understood whether it is possible to make effective, general and universal models in biology. Nevertheless, modeling all the details of a biological process is usually redundant and has too many parameters.

We try to look at this concretely in the case of embryonic development. Embryonic development is a complex phenomena involving growth, differentiation and morphogenesis. The basic control mechanism for how a cell fate is specified is set by gene regulatory networks. Such networks however have nonlinear interactions which are rarely measured in any quantitative manner. Typical models try to model the details of the gene regulatory network and suffer from being over-parameterized.

Experimental embryology from the 1950s instead developed a different understanding of development, with "morphogenetic fields" and "Waddington landscapes" which conceptually was very similar to emergence. I work on how to mathematically model these landscapes and fit them to experimental data (https://www.pnas.org/doi/10.1073/pnas.2109729118). These landscapes are an emergent description which typically involve fewer parameters and are more universal (https://onlinelibrary.wiley.com/doi/abs/10.1111/dgd.12855). How they relate to the underlying regulatory network is an open question. We are thinking of this for different systems from early stages of the mouse embryo to the robustness of the number of digits in your hand.

Furthermore I am interested in how the mathematical description of evolution changes when development is added, including genetic assimilation and phenotypic plasticity (https://www.pnas.org/doi/10.1073/pnas.2309760120).

Note: Our work is purely theoretical. If you are interested in the work, you can write to me but you have to have a mathematics/physics/engineering background.