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Photo of Tobias Ambjörnsson

Tobias Ambjörnsson

Senior lecturer

Photo of Tobias Ambjörnsson

Achieving subtemporal resolution in the analysis of two-state single-molecule trajectories

Author

  • Erik Clarkson
  • Tobias Ambjörnsson

Summary, in English

Although spatial resolution in fluorescence microscopy and related fields has advanced to the nanometer scale, time resolution has remained essentially unchanged and is set by the camera system’s imaging time. Yet adequate time resolution is crucial for information acquisition about, for instance, dynamical processes in cells. This acquisition typically proceeds by analyzing biomolecular trajectories from single-particle tracking experiments, in terms of a standard discrete-time hidden Markov model. This type of analysis assumes, however, that subsampling time events that happen during imaging time can be neglected, which is rarely the case. To remedy this, we here introduce an algorithm that efficiently calculates the exact contribution of state switches to the likelihood of observed trajectories. This is made possible by our analytic derivation of generalized transition probabilities—which we call transition-accretion probabilities—that probabilistically capture unseen switching behavior during data acquisition. We do in-silico Bayesian model selection and parameter inference, and demonstrate that our subsampling time hidden Markov model approach outperforms the standard variant (applicable to slow kinetics). Our method and associated free-to-use software opens up for precise and reliable parameter estimation across a variety of single-molecule experiments, irrespective of the temporal resolution of the setup.

Department/s

  • Centre for Environmental and Climate Science (CEC)
  • Computational Science for Health and Environment
  • Department of Earth and Environmental Sciences (MGeo)

Publishing year

2026-01-30

Language

English

Pages

013115-013115

Publication/Series

Physical Review Research

Volume

8

Issue

1

Document type

Journal article

Publisher

American Physical Society

Topic

  • Biophysics
  • Statistical physics and complex systems

Status

Published

Project

  • Probabilistic analysis of fluorescence trajectories

Research group

  • Computational Science for Health and Environment

ISBN/ISSN/Other

  • ISSN: 2643-1564