Bayesian Inference: The Comprehensive Approach to Analyzing Single-Molecule Experiments.

ABSTRACT: Biophysics experiments performed at single-molecule resolution provide exceptional insight into the structural details and dynamic behavior of biological systems. However, extracting this information from the corresponding experimental data unequivocally requires applying a biophysical model. In this review, we discuss how to use probability theory to apply these models to single-molecule data. Many current single-molecule data analysis methods apply parts of probability theory, sometimes unknowingly, and thus miss out on the full set of benefits provided by this self-consistent framework. The full application of probability theory involves a process called Bayesian inference that fully accounts for the uncertainties inherent to single-molecule experiments. Additionally, using Bayesian inf

SUBMITTER: Kinz-Thompson CD 

PROVIDER: S-EPMC8238404 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature