Life is complicated and full of uncertainties. Researchers stand at the frontier, facing uncertainty in its most fundamental form. Instead of succumbing to the great complexity, researchers “developed the art of describing uncertainty in terms of probabilistic models, as well as the skill of probabilistic reasoning” (Bertsekas and Tsitsiklis).
The use of probability theory transformed science altogether, from quantum chemistry to neuroscience. One major component which repeats in many works is the failure of old “macroscopic” mean-field theories to accurately depict biological systems. In many such systems, molecules are present in nanomolar concentrations such that fluctuations in the spatial distributions, encounter times and reactivities cannot be disregarded. Anomalous transport properties, morphological effects and many-particle phenomena complicate the picture even further.
My PhD years were dedicated to creating a general toolkit that can treat complex interactions of molecules with the environment and its boundaries, as well as the intricate internal dynamics of the molecules themselves and their effect on reactivity/activity. So far, I have focused on gating, stickiness, and exchange. I did so on the single-molecule level, exploring the aforementioned probabilistic effects analytically and using simulations. The generality of the tools I have developed lies in the derivation of “plug and play” equations that express the solution for a model with complicated dressed dynamics (e.g., diffusion with gating) in terms of the solution for the much simpler underlying model (e.g., free diffusion). Thus, researchers can quickly attain the solution for various dressed models from known or easy to solve models of the underlying dynamics. Furthermore, this bottom-up approach can be used to unify micro- and macroscopic descriptions.
Going forward, I wish to create a more symbiotic relationship between my theoretical research and modern observations of biological systems.
Yuval Scher 