Reconstruction of stochastic differential equations characterizing noisy single-cell molecular dynamics

In the talk, I shall introduce our recent work on developing machine-learning-based methods for reconstructing noisy single-cell molecular dynamics as stochastic differential equations, which aims to quantify intrinsic fluctuations in the stochastic process characterizing cellular dynamics. I will then discuss how to apply my methods to reconstruct stochastic processes in cellular dynamics such as the Langevin dynamics and fluctuations in protein count from data.