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- W3133289272 abstract "Fluorescence spectroscopy is a great way to reveal complex interactions at the molecular level, but because fluorophores are much smaller than the diffraction limit of light, one bright spot may contain many fluorescently labeled biomolecules. One technique to quantify the number of molecules within a diffraction limited spot is to illuminate the spot, putting the fluorophores into their fluorescently active bright states, then to watch for steplike brightness drops as the fluorophores photobleach one-by-one. This analysis is impeded by detector noise, shot noise, and by the fact that fluorophores can have dark states and multiple bright states. Furthermore, because the number of fluorophores is unknown, we cannot utilize traditional Bayesian methods to count and we must invoke new methods to solve the problem. Here we use Bayesian nonparametric (BNP) tools, that are necessary as the number of fluorophores is unknown, to solve the counting problem. We conclude that our method allows us to count upwards of 100 fluorophores. Single molecule Forster resonance energy transfer (FRET) based fluorescence experiments are a useful way to probe configuration dynamics of molecules based on the distance between donor and acceptor labels. Here we show that we can use single photon information to extract potential profiles from molecules of interest. We do so using Gaussian processes, a powerful tool within BNPs" @default.
- W3133289272 created "2021-03-01" @default.
- W3133289272 creator A5090677228 @default.
- W3133289272 date "2021-02-01" @default.
- W3133289272 modified "2023-09-25" @default.
- W3133289272 title "Counting Fluorophores and Finding Potentials from FRET, Bayesian Nonparametrics for Challenging Problems in Biophysics" @default.
- W3133289272 doi "https://doi.org/10.1016/j.bpj.2020.11.1274" @default.
- W3133289272 hasPublicationYear "2021" @default.
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