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Robust Bayesian Fluorescence Lifetime Estimation, Decay Model Selection and Instrument Response Determination for
Mark I Rowley1, Anthonius C C Coolen1, Borivoj Vojnovic2
1Institute for Mathematical and Molecular Biomedicine, King's College London, London, United Kingdom.
Plos One
|June 30, 2016
Summary
We developed new Bayesian methods to analyze exponential decay data, improving accuracy by up to 50% for fluorescence lifetime imaging microscopy (FLIM) and Förster Resonance Energy Transfer (FRET) experiments.
Area of Science:
- Biophysics
- Computational Science
- Microscopy
Background:
- Accurate analysis of exponential decay data is crucial in fields like fluorescence lifetime imaging microscopy (FLIM).
- Existing methods for analyzing time-correlated single photon counting (TCSPC) data have limitations in accuracy and advanced processing capabilities.
Purpose of the Study:
- To present novel Bayesian methods for analyzing exponential decay data with improved accuracy.
- To demonstrate advanced processing techniques including decay model selection and simultaneous parameter estimation.
Main Methods:
- Development of Bayesian algorithms that utilize evidence from every detected decay event.
- Accurate modeling of time-domain systems using time-correlated single photon counting (TCSPC).
- Application of methods to mono- and bi-exponential decay systems.
Main Results:
- Achieved up to a factor of two improvement in accuracy for decay parameter estimation compared to previous techniques.
- Demonstrated superior precision applicable to Förster Resonance Energy Transfer (FRET) experiments.
- Successfully implemented decay model selection and simultaneous estimation of instrument and decay parameters.
Conclusions:
- The presented Bayesian methods offer a significant advancement in the analysis of exponential decay data.
- These techniques provide enhanced accuracy and enable sophisticated data processing for FLIM and FRET applications.
