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Single-photon smFRET: II. Application to continuous illumination
Here we adapt the Bayesian nonparametrics (BNP) framework presented in the first companion article to analyze kinetics from single-photon, single-molecule Förster resonance energy transfer (smFRET) traces generated under continuous illumination. Using our sampler, BNP-FRET, we learn the escape rates...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9792399/ https://www.ncbi.nlm.nih.gov/pubmed/36582656 http://dx.doi.org/10.1016/j.bpr.2022.100087 |
_version_ | 1784859627570069504 |
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author | Saurabh, Ayush Safar, Matthew Fazel, Mohamadreza Sgouralis, Ioannis Pressé, Steve |
author_facet | Saurabh, Ayush Safar, Matthew Fazel, Mohamadreza Sgouralis, Ioannis Pressé, Steve |
author_sort | Saurabh, Ayush |
collection | PubMed |
description | Here we adapt the Bayesian nonparametrics (BNP) framework presented in the first companion article to analyze kinetics from single-photon, single-molecule Förster 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. |
format | Online Article Text |
id | pubmed-9792399 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-97923992022-12-28 Single-photon smFRET: II. Application to continuous illumination Saurabh, Ayush Safar, Matthew Fazel, Mohamadreza Sgouralis, Ioannis Pressé, Steve Biophys Rep (N Y) Article Here we adapt the Bayesian nonparametrics (BNP) framework presented in the first companion article to analyze kinetics from single-photon, single-molecule Förster 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. Elsevier 2022-12-02 /pmc/articles/PMC9792399/ /pubmed/36582656 http://dx.doi.org/10.1016/j.bpr.2022.100087 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Saurabh, Ayush Safar, Matthew Fazel, Mohamadreza Sgouralis, Ioannis Pressé, Steve Single-photon smFRET: II. Application to continuous illumination |
title | Single-photon smFRET: II. Application to continuous illumination |
title_full | Single-photon smFRET: II. Application to continuous illumination |
title_fullStr | Single-photon smFRET: II. Application to continuous illumination |
title_full_unstemmed | Single-photon smFRET: II. Application to continuous illumination |
title_short | Single-photon smFRET: II. Application to continuous illumination |
title_sort | single-photon smfret: ii. application to continuous illumination |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9792399/ https://www.ncbi.nlm.nih.gov/pubmed/36582656 http://dx.doi.org/10.1016/j.bpr.2022.100087 |
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