State estimation of yeast galactose pathway using extended Kalman filter

Abstract

Biological Systems pertain to problems relative to disturbances, since various outputs (Proteins, Signals, Polymer Complexes etc.) are usually adulterated due to extrinsic and intrinsic uncertainties. Thus, standard estimation processes turns out significant in such scenarios where states/parameters could be estimated in order to accurately define the measurements. In this paper, a standard Extended Kalman filtering (EKF) approach has been implemented in order to estimate the states of a yeast galactose pathway, operating in constantly changing sources of nutrients.