Statistical inference for a multiscale stochastic model of enzyme kinetics via propagation of chaos
The paper develops a method to estimate enzyme kinetic parameters using only random samples of product formation times, bypassing the need for full system trajectories. It uses an Interacting Particle System and propagation of chaos to create a simplified model that links observed data directly to parameter estimation, achieving consistent results.