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Likelihood functions for the analysis of single-molecule binned photon sequences
1Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892, USA.
Chemical Physics
|June 20, 2012
Summary
This study develops a likelihood-based method for analyzing photon count data from experiments, offering an improved approach for understanding molecular dynamics and FRET efficiencies.
Area of Science:
- Biophysics
- Chemical Physics
- Physical Chemistry
Background:
- Photon counting experiments record light emission over time.
- Analyzing sequences of photon counts or FRET efficiencies is crucial for understanding molecular dynamics.
- Existing methods like hidden Markov models have limitations in accuracy.
Purpose of the Study:
- To develop a formalism for calculating the exact likelihood of kinetic models describing photon count or FRET efficiency sequences.
- To provide explicit analytic expressions for a two-state kinetic model.
- To investigate approximations and derive an improved likelihood function.
Main Methods:
- Development of a likelihood-based formalism for kinetic models.
- Calculation of exact likelihood for photon count and FRET efficiency sequences.
- Derivation of analytic expressions for a two-state kinetic model.
Main Results:
- An exact likelihood formalism is developed for analyzing photon count and FRET efficiency data.
- Analytic expressions for a two-state kinetic model are derived.
- Approximations lead to the recovery of hidden Markov model likelihoods, revealing their range of validity.
Conclusions:
- The developed method provides an improved likelihood function for analyzing molecular dynamics from photon data.
- The study offers insights into the accuracy and limitations of hidden Markov models in this context.
- This work enhances the analysis of conformational dynamics in biophysical experiments.
