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Two lifetimes smaller than the IRF width(σ IRF = 0.66 ns). (a-c) Marginal posterior of lifetime with 500, 1K and 5K photons, respectively.
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Fluorescence lifetime imaging (FLIM) has been essential in capturing spatial distributions of chemical species across cellular environments employing pulsed illumination confocal setups. However, quantitative interpretation of lifetime data continues to face critical challenges. For instance, fluorescent species with known in vitro excited state li...
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... copyright holder for this preprint this version posted September 12, 2022. ; https://doi.org/10.1101/2022.09.08.507224 doi: bioRxiv preprint both lifetimes (see Fig. 4a). Increasing the photon budget to 1K and 5K, our method begins attributing non-negligible weights to two lifetimes whose sum is larger than 0.9 (see Fig. 4bc). We also note that the uncertainties over the estimated lifetimes decrease with increasing photon ...
Context 2
... copyright holder for this preprint this version posted September 12, 2022. ; https://doi.org/10.1101/2022.09.08.507224 doi: bioRxiv preprint both lifetimes (see Fig. 4a). Increasing the photon budget to 1K and 5K, our method begins attributing non-negligible weights to two lifetimes whose sum is larger than 0.9 (see Fig. 4bc). We also note that the uncertainties over the estimated lifetimes decrease with increasing photon ...
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Citations
... Within this iHMM framework, we place an infinite dimensional version of the Dirichlet prior, termed the Dirichlet process prior (41,48,78), as priors over each row of the propagator P s . That is, ...
We present a unified conceptual framework and the associated software package for single molecule Förster Resonance Energy Transfer (smFRET) analysis from single photon arrivals leveraging Bayesian nonparametrics, BNP-FRET. This unified framework addresses the following key physical complexities of a single photon smFRET experiment, including: 1) fluorophore photophysics; 2) continuous time kinetics of the labeled system with large timescale separations between photophysical phenomena such as excited photophysical state lifetimes and events such as transition between system states; 3) unavoidable detector artefacts; 4) background emissions; 5) unknown number of system states; and 6) both continuous and pulsed illumination. These physical features necessarily demand a novel framework that extends beyond existing tools. In particular, the theory naturally brings us to a hidden Markov model (HMM) with a second order structure and Bayesian nonparametrics (BNP) on account of items 1, 2 and 5 on the list. In the second and third companion manuscripts, we discuss the direct effects of these key complexities on the inference of parameters for continuous and pulsed illumination, respectively.
... Moreover, g is a positive scalar hyperparameter of the Dirichlet process prior often chosen to be one. As such, we ascribe identical weights across the state space a priori for computational convenience (28,29,49). Now, equipped with the nonparametric posterior, we proceed to simultaneously make inferences on transition probabilities, excited-state escape rates, and the remaining parameters. ...
Förster resonance energy transfer (FRET) using pulsed illumination has been pivotal in leveraging lifetime information in FRET analysis. However, there remain major challenges in quantitative single photon, single molecule FRET (smFRET) data analysis under pulsed illumination including: 1) simultaneously deducing kinetics and number of system states; 2) providing uncertainties over estimates, particularly uncertainty over the number of system states; 3) taking into account detector noise sources such as crosstalk, and the instrument response function contributing to uncertainty; in addition to 4) other experimental noise sources such as background. Here, we implement the Bayesian nonparametric framework described in the first companion manuscript that addresses all aforementioned issues in smFRET data analysis specialized for the case of pulsed illumination. Furthermore, we apply our method to both synthetic as well as experimental data acquired using Holliday junctions.
