The towering successes of twentieth century theoretical physics were marked by two guiding principles: symmetry and energy functionals (reflecting equilibrium dynamics). Yet, outside some limited settings it remains unclear how we can exploit these principles to develop a theory of living systems since biology is full of heterogeneous, interacting components operating out of equilibrium. In this talk, I will argue that one possible strategy for taming biological complexity is to embrace the idea that many biological behaviors we observe are “typical” and can be modeled using random systems augmented with biologically inspired constraints. I will focus on showing how this approach can be used to make close connection with experiments by presenting three vignettes focusing on: (i) theory-inspired techniques for visualizing single-cell transcriptomics data for cellular identity, (ii) understanding how the interplay between cross-feeding and competition shapes microbial ecosystems, and (iii) a theoretical analysis exploring a possible “algorithm” implemented by Tregs to help the immune system perform self /non-self discrimination.
Bio: Pankaj Mehta is Professor of Physics and a member of the Faculty of Computing and Data Science at Boston University. He is interested in theoretical problems at the interface of statistical physics and biology, (and sometimes machine learning).