@article{bd02f6788c4845d7b2cd9025ca094a95,
title = "Single-photon smFRET: II. Application to continuous illumination",
abstract = "Here we adapt the Bayesian nonparametrics (BNP) framework presented in the first companion article to analyze kinetics from single-photon, single-molecule F{\"o}rster resonance energy transfer (smFRET) traces generated under continuous illumination. Using our sampler, BNP-FRET, we learn the escape rates and the number of system states given a photon trace. We benchmark our method by analyzing a range of synthetic and experimental data. Particularly, we apply our method to simultaneously learn the number of system states and the corresponding kinetics for intrinsically disordered proteins using two-color FRET under varying chemical conditions. Moreover, using synthetic data, we show that our method can deduce the number of system states even when kinetics occur at timescales of interphoton intervals.",
author = "Ayush Saurabh and Matthew Safar and Mohamadreza Fazel and Ioannis Sgouralis and Steve Press{\'e}",
note = "Funding Information: We thank Weiqing Xu and Dr. Zeliha Kilic for regular feedback and help, especially during the development of the nonparametrics samplers. We also thank Prof. Benjamin Schuler, Dr. Daniel Nettels, and Oliver Stach for regular feedback and providing the necessary experimental data. S.P. acknowledges support from the NIH NIGMS ( R01GM130745 ) for supporting early efforts in nonparametrics and NIH NIGMS ( R01GM134426 ) for supporting single-photon efforts. The majority of the computations were performed on the Agave and Sol supercomputers at ASU. Funding Information: We thank Weiqing Xu and Dr. Zeliha Kilic for regular feedback and help, especially during the development of the nonparametrics samplers. We also thank Prof. Benjamin Schuler, Dr. Daniel Nettels, and Oliver Stach for regular feedback and providing the necessary experimental data. S.P. acknowledges support from the NIH NIGMS (R01GM130745) for supporting early efforts in nonparametrics and NIH NIGMS (R01GM134426) for supporting single-photon efforts. The majority of the computations were performed on the Agave and Sol supercomputers at ASU. The authors declare no competing interests. Publisher Copyright: {\textcopyright} 2022 The Authors",
year = "2023",
month = mar,
day = "8",
doi = "10.1016/j.bpr.2022.100087",
language = "English (US)",
volume = "3",
journal = "Biophysical Reports",
issn = "2667-0747",
publisher = "Tabriz University of Medical Sciences",
number = "1",
}