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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-10-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/24/20/15074 |
| _version_ | 1797573689866190848 |
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| author | Van N. T. La David D. L. Minh |
| author_facet | Van N. T. La David D. L. Minh |
| author_sort | Van N. T. La |
| collection | DOAJ |
| description | 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 interval. When the methods are applied to simulated experiments and to measurements of Mg(II) binding to EDTA, the asymptotic standard error underestimates the uncertainty in the free energy and enthalpy of binding. Error propagation overestimates the uncertainty for both quantities, except in the simulations, where it underestimates the uncertainty of enthalpy for confidence intervals less than 70%. In both datasets, Bayesian credible intervals are much closer to observed confidence intervals. |
| first_indexed | 2024-03-10T21:12:35Z |
| format | Article |
| id | doaj.art-3ea79e8bf83743a494525d4db8165afc |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-10T21:12:35Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-3ea79e8bf83743a494525d4db8165afc2023-11-19T16:41:14ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672023-10-0124201507410.3390/ijms242015074Bayesian Regression Quantifies Uncertainty of Binding Parameters from Isothermal Titration Calorimetry More Accurately Than Error PropagationVan N. T. La0David D. L. Minh1Department of Biology, Illinois Institute of Technology, Chicago, IL 60616, USADepartment of Chemistry, Illinois Institute of Technology, Chicago, IL 60616, USAWe 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 interval. When the methods are applied to simulated experiments and to measurements of Mg(II) binding to EDTA, the asymptotic standard error underestimates the uncertainty in the free energy and enthalpy of binding. Error propagation overestimates the uncertainty for both quantities, except in the simulations, where it underestimates the uncertainty of enthalpy for confidence intervals less than 70%. In both datasets, Bayesian credible intervals are much closer to observed confidence intervals.https://www.mdpi.com/1422-0067/24/20/15074Isothermal Titration Calorimetry (ITC)Bayesian Credible Interval (BCI)Confidence Interval (CI)Asymptotic Standard Error (ASE)Maximum Likelihood Estimation (MLE)Error Propagation (EP) |
| spellingShingle | Van N. T. La David D. L. Minh Bayesian Regression Quantifies Uncertainty of Binding Parameters from Isothermal Titration Calorimetry More Accurately Than Error Propagation International Journal of Molecular Sciences Isothermal Titration Calorimetry (ITC) Bayesian Credible Interval (BCI) Confidence Interval (CI) Asymptotic Standard Error (ASE) Maximum Likelihood Estimation (MLE) Error Propagation (EP) |
| title | Bayesian Regression Quantifies Uncertainty of Binding Parameters from Isothermal Titration Calorimetry More Accurately Than Error Propagation |
| title_full | Bayesian Regression Quantifies Uncertainty of Binding Parameters from Isothermal Titration Calorimetry More Accurately Than Error Propagation |
| title_fullStr | Bayesian Regression Quantifies Uncertainty of Binding Parameters from Isothermal Titration Calorimetry More Accurately Than Error Propagation |
| title_full_unstemmed | Bayesian Regression Quantifies Uncertainty of Binding Parameters from Isothermal Titration Calorimetry More Accurately Than Error Propagation |
| title_short | Bayesian Regression Quantifies Uncertainty of Binding Parameters from Isothermal Titration Calorimetry More Accurately Than Error Propagation |
| title_sort | bayesian regression quantifies uncertainty of binding parameters from isothermal titration calorimetry more accurately than error propagation |
| topic | Isothermal Titration Calorimetry (ITC) Bayesian Credible Interval (BCI) Confidence Interval (CI) Asymptotic Standard Error (ASE) Maximum Likelihood Estimation (MLE) Error Propagation (EP) |
| url | https://www.mdpi.com/1422-0067/24/20/15074 |
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