Bayesian parameter estimation for dynamical models in systems biology.

ABSTRACT: Dynamical systems modeling, particularly via systems of ordinary differential equations, has been used to effectively capture the temporal behavior of different biochemical components in signal transduction networks. Despite the recent advances in experimental measurements, including sensor development and '-omics' studies that have helped populate protein-protein interaction networks in great detail, modeling in systems biology lacks systematic methods to estimate kinetic parameters and quantify associated uncertainties. This is because of multiple reasons, including sparse and noisy experimental measurements, lack of detailed molecular mechanisms underlying the reactions, and missing biochemical interactions. Additionally, the inherent nonlinearities with respect to the states and parame

SUBMITTER: Linden NJ 

PROVIDER: S-EPMC9629650 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature