Bayesian Regression Quantifies Uncertainty of Binding Parameters from Isothermal Titration Calorimetry More Accurately Than Error Propagation

Bayesian Regression Quantifies Uncertainty of Binding Parameters from Isothermal Titration Calorimetry More Accurately Than Error Propagation

We compare several different methods to quantify the uncertainty of binding parameters estimated from isothermal titration calorimetry data: the asymptotic standard error from maximum likelihood estimation, error propagation based on a first-order Taylor series expansion, and the Bayesian credible i...

Full description

Bibliographic Details
Main Authors: Van N. T. La, David D. L. Minh
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:International Journal of Molecular Sciences
Subjects:
Isothermal Titration Calorimetry (ITC)
Bayesian Credible Interval (BCI)
Confidence Interval (CI)
Asymptotic Standard Error (ASE)
Maximum Likelihood Estimation (MLE)
Error Propagation (EP)
Online Access:https://www.mdpi.com/1422-0067/24/20/15074

Internet

https://www.mdpi.com/1422-0067/24/20/15074

Similar Items