ArticleCell reports. Physical science2021
Extraction of rapid kinetics from smFRET measurements using integrative detectors.
Article in Cell reports. Physical science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- A cautious user's guide in applying HMMs to physical systems.The Journal of chemical physics · 2025Article
- Single-Photon Single-Particle Tracking.bioRxiv : the preprint server for biology · 2025Article
- Quantitative Assessment of Biological Dynamics with Aggregate Data.Bulletin of mathematical biology · 2025Article
- Bayesian analysis and efficient algorithms for single-molecule fluorescence data and step counting.Biophysical journal · 2025Article
- Bayesian analysis and efficient algorithms for single-molecule fluorescence data and step counting.bioRxiv : the preprint server for biology · 2025Article
- Physics-Inspired Single-Particle Tracking Accelerated with Parallelism.bioRxiv : the preprint server for biology · 2025Article
- Single-molecule reaction-diffusion.Biophysical journal · 2025Article
- Bayesian Inference of Binding Kinetics from Fluorescence Time Series.The journal of physical chemistry. B · 2025Article
- Using Bayesian priors to overcome non-identifiablility issues in Hidden Markov models.bioRxiv : the preprint server for biology · 2025Article
- An accurate probabilistic step finder for time-series analysis.Biophysical journal · 2024Article
- BNP-Track: a framework for superresolved tracking.Nature methods · 2024Article
- Article
- Single-Molecule Reaction-Diffusion.bioRxiv : the preprint server for biology · 2023Article
- Single-photon smFRET: II. Application to continuous illumination.Biophysical reports · 2023Article
- Single-photon smFRET. I: Theory and conceptual basis.Biophysical reports · 2023Article
- Gene expression model inference from snapshot RNA data using Bayesian non-parametrics.Nature computational science · 2023Article
- Single-photon smFRET. III. Application to pulsed illumination.Biophysical reports · 2022Article
- The Effect of Time Resolution on Apparent Transition Path Times Observed in Single-Molecule Studies of Biomolecules.The journal of physical chemistry. B · 2022Article
- Inferring potential landscapes from noisy trajectories of particles within an optical feedback trap.iScience · 2022Article
- Heterogeneous migration routes of DNA triplet repeat slip-outs.Biophysical reports · 2022Article
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Authors and funding
6 authors.
Funding
Abstract
Hidden Markov models (HMMs) are used to learn single-molecule kinetics across a range of experimental techniques. By their construction, HMMs assume that single-molecule events occur on slower timescales than those of data acquisition. To move beyond that HMM limitation and allow for single-molecule events to occur on any timescale, we must treat single-molecule events in continuous time as they occur in nature. We propose a method to learn kinetic rates from single-molecule Förster resonance energy transfer (smFRET) data collected by integrative detectors, even if those rates exceed data acquisition rates. To achieve that, we exploit our recently proposed "hidden Markov jump process" (HMJP), with which we learn transition kinetics from parallel measurements in donor and acceptor channels. HMJPs generalize the HMM paradigm in two critical ways: (1) they deal with physical smFRET systems as they switch between conformational states in
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.