ArticleThe Journal of cell biology2023
ExTrack characterizes transition kinetics and diffusion in noisy single-particle tracks.
Article in The Journal of cell biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 34 citations in OpenAlex.
- Mechanistic trade-offs between local and long-range signaling activity in natural and synthetic morphogens.Science advances · 2026Article
- Review of Machine Learning for Single-Particle Tracking: Methods, Challenges, and Biophysical Insights.Chemical & biomedical imaging · 2026Review
- Detecting directed motion and confinement in single-particle trajectories using hidden variables.eLife · 2026Article
- Multicolor Quantum Dot Tracking Uncovers Phenotypic Rescue of DAT A559V Aberrant Diffusion Upon D2R Antagonism.ACS chemical neuroscience · 2026Article
- Accurate Single-Particle Tracking and Diffusion Measurement in Freestanding Lipid Bilayers and Model Membranes.Analytical chemistry · 2025Article
- Revealing plasma membrane protein dynamics in living plant cells with single-molecule tracking.Journal of experimental botany · 2025Article
- TRF1 and TRF2 form distinct shelterin subcomplexes at telomeres.Cell reports · 2025Article
- Deep learning-assisted analysis of single-particle tracking for automated correlation between diffusion and function.Nature methods · 2025Article
- Nuclear basket proteins regulate the distribution and mobility of nuclear pore complexes in budding yeast.Molecular biology of the cell · 2024Article
- Diffusion barriers imposed by tissue topology shape Hedgehog morphogen gradients.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Robust Quantification of Live-Cell Single-Molecule Tracking Data for Fluorophores with Different Photophysical Properties.The journal of physical chemistry. B · 2024Article
- Article
- Review
- Single-molecule imaging in the primary cilium.Methods in cell biology · 2023Article
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Authors and funding
3 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-particle tracking microscopy is a powerful technique to investigate how proteins dynamically interact with their environment in live cells. However, the analysis of tracks is confounded by noisy molecule localization, short tracks, and rapid transitions between different motion states, notably between immobile and diffusive states. Here, we propose a probabilistic method termed ExTrack that uses the full spatio-temporal information of tracks to extract global model parameters, to calculate state probabilities at every time point, to reveal distributions of state durations, and to refine the positions of bound molecules. ExTrack works for a wide range of diffusion coefficients and transition rates, even if experimental data deviate from model assumptions. We demonstrate its capacity by applying it to slowly diffusing and rapidly transitioning bacterial envelope proteins. ExTrack greatly increases the regime of computationally analyzable noisy single-particle tracks. The ExTrack package is available in ImageJ and Python.
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Registered trials
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.