ArticlePLoS computational biology2009
A hidden Markov model for single particle tracks quantifies dynamic interactions between LFA-1 and the actin cytoskeleton.
Article in PLoS computational biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.
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Who cites it
57 citing papers in PubMed.
- Single-trajectory Bayesian modeling reveals multi-state diffusion of the MSH sliding clamp.NPJ systems biology and applications · 2026Article
- Photophysics of Organic Fluorophore Photobluing and Its Applications in Fluorescence and Super-Resolution Microscopy.Accounts of chemical research · 2026Article
- Multicolor Quantum Dot Tracking Uncovers Phenotypic Rescue of DAT A559V Aberrant Diffusion Upon D2R Antagonism.ACS chemical neuroscience · 2026Article
- Revealing plasma membrane protein dynamics in living plant cells with single-molecule tracking.Journal of experimental botany · 2025Article
- Trajectory Analysis in Single-Particle Tracking: From Mean Squared Displacement to Machine Learning Approaches.International journal of molecular sciences · 2024Review
- Robust Quantification of Live-Cell Single-Molecule Tracking Data for Fluorophores with Different Photophysical Properties.The journal of physical chemistry. B · 2024Article
- Extract latent features of single-particle trajectories with historical experience learning.Biophysical journal · 2023Article
- Recent Advances in Single-Molecule Tracking and Imaging Techniques.Annual review of analytical chemistry (Palo Alto, Calif.) · 2023Review
- Uncovering diffusive states of the yeast membrane protein, Pma1, and how labeling method can change diffusive behavior.The European physical journal. E, Soft matter · 2023Article
- Article
- ExTrack characterizes transition kinetics and diffusion in noisy single-particle tracks.The Journal of cell biology · 2023Article
- Palmitate-mediated disruption of the endoplasmic reticulum decreases intracellular vesicle motility.Biophysical journal · 2023Article
- Simulation-based inference for non-parametric statistical comparison of biomolecule dynamics.PLoS computational biology · 2023Article
- Single-molecule analysis of intracellular insulin granule behavior and its application to analyzing cytoskeletal dependence and pathophysiological implications.Frontiers in physiology · 2023Article
- Receptor tyrosine kinase MET ligand-interaction classified via machine learning from single-particle tracking data.Molecular biology of the cell · 2022Article
- Spiracular fluttering decouples oxygen uptake and water loss: a stochastic PDE model of respiratory water loss in insects.Journal of mathematical biology · 2022Article
- Triple-color single-molecule imaging for analysis of the role of receptor oligomers in signal transduction.Biophysics and physicobiology · 2022Article
- A pairwise distance distribution correction (DDC) algorithm to eliminate blinking-caused artifacts in SMLM.Nature methods · 2021Article
- Detection of Anomalous Diffusion with Deep Residual Networks.Entropy (Basel, Switzerland) · 2021Article
- Fundamentals of the logarithmic measure for revealing multimodal diffusion.Biophysical journal · 2021Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The extraction of hidden information from complex trajectories is a continuing problem in single-particle and single-molecule experiments. Particle trajectories are the result of multiple phenomena, and new methods for revealing changes in molecular processes are needed. We have developed a practical technique that is capable of identifying multiple states of diffusion within experimental trajectories. We model single particle tracks for a membrane-associated protein interacting with a homogeneously distributed binding partner and show that, with certain simplifying assumptions, particle trajectories can be regarded as the outcome of a two-state hidden Markov model. Using simulated trajectories, we demonstrate that this model can be used to identify the key biophysical parameters for such a system, namely the diffusion coefficients of the underlying states, and the rates of transition between them. We use a stochastic optimization scheme to compute maximum likelihood estimates of these parameters. We have applied this analysis to single-particle trajectories of the integrin receptor lymphocyte function-associated antigen-1 (LFA-1) on live T cells. Our analysis reveals that the diffusion of LFA-1 is indeed approximately two-state, and is characterized by large changes in cytoskeletal interactions upon cellular activation.
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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.