ArticleBiophysical journal2001
Anomalous subdiffusion in fluorescence photobleaching recovery: a Monte Carlo study.
Article in Biophysical journal, 2001. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers.
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Who cites it
81 citing papers in PubMed.
- Feature Selection and Hyperparameter Optimization for Machine Learned Classification of 3D Single-Particle Tracking.Chemical & biomedical imaging · 2026Article
- Water transport mechanisms during pressure-driven transport through polyamide nanogaps.Physics of fluids (Woodbury, N.Y. : 1994) · 2025Article
- Simulation Studies of Dynamical Heterogeneity in a Dense Two-Dimensional Dimer-Solvent System with Obstacles.Entropy (Basel, Switzerland) · 2024Article
- Record ages of non-Markovian scale-invariant random walks.Nature communications · 2023Article
- What's past is prologue: FRAP keeps delivering 50 years later.Biophysical journal · 2023Review
- Expanding the applicability of multiphoton fluorescence recovery after photobleaching by incorporating shear stress in laminar flow.Journal of biomedical optics · 2023Article
- Bayesian deep learning for error estimation in the analysis of anomalous diffusion.Nature communications · 2022Article
- Inferences from FRAP data are model dependent: A subdiffusive analysis.Biophysical journal · 2022Article
- The TFIIH subunits p44/p62 act as a damage sensor during nucleotide excision repair.Nucleic acids research · 2020Article
- Diffusion of DNA-Binding Species in the Nucleus: A Transient Anomalous Subdiffusion Model.Biophysical journal · 2020Article
- Controlling Anomalous Diffusion in Lipid Membranes.Biophysical journal · 2019Article
- Motion in a crowded environment: the influence of obstacles' size and shape and model of transport.Journal of molecular modeling · 2019Article
- Urea-mediated anomalous diffusion in supported lipid bilayers.Interface focus · 2018Article
- Numerical Simulation and FRAP Experiments Show That the Plasma Membrane Binding Protein PH-EFA6 Does Not Exhibit Anomalous Subdiffusion in Cells.Biomolecules · 2018Article
- Bioengineering of a Full-Thickness Skin Equivalent in a 96-Well Insert Format for Substance Permeation Studies and Organ-On-A-Chip Applications.Bioengineering (Basel, Switzerland) · 2018Article
- Multistep Track Segmentation and Motion Classification for Transient Mobility Analysis.Biophysical journal · 2018Article
- Rad4 recognition-at-a-distance: Physical basis of conformation-specific anomalous diffusion of DNA repair proteins.Progress in biophysics and molecular biology · 2017Review
- Review
- Classification and Segmentation of Nanoparticle Diffusion Trajectories in Cellular Micro Environments.PloS one · 2017Article
- Underdamped scaled Brownian motion: (non-)existence of the overdamped limit in anomalous diffusion.Scientific reports · 2016Article
21 more citing papers are in PubMed but not listed here.
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Abstract
Anomalous subdiffusion is hindered diffusion in which the mean-square displacement of a diffusing particle is proportional to some power of time less than one. Anomalous subdiffusion has been observed for a variety of lipids and proteins in the plasma membranes of a variety of cells. Fluorescence photobleaching recovery experiments with anomalous subdiffusion are simulated to see how to analyze the data. It is useful to fit the recovery curve with both the usual recovery equation and the anomalous one, and to judge the goodness of fit on log-log plots. The simulations show that the simplest approximate treatment of anomalous subdiffusion usually gives good results. Three models of anomalous subdiffusion are considered: obstruction, fractional Brownian motion, and the continuous-time random walk. The models differ significantly in their behavior at short times and in their noise level. For obstructed diffusion the approach to the percolation threshold is marked by a large increase in noise, a broadening of the distribution of diffusion coefficients and anomalous subdiffusion exponents, and the expected abrupt decrease in the mobile fraction. The extreme fluctuations in the recovery curves at and near the percolation threshold result from extreme fluctuations in the geometry of the percolation cluster.
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