{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["116(5)"],"submitter":["Stolle MDN"],"funding":["Natural Sciences and Engineering Research Council of Canada"],"pubmed_abstract":["Using fluorescence correlation spectroscopy (FCS) to distinguish between different types of diffusion processes is often a perilous undertaking because the analysis of the resulting autocorrelation data is model dependant. Two recently introduced strategies, however, can help move toward a model-independent interpretation of FCS experiments: 1) the obtention of correlation data at different length scales and 2) their inversion to retrieve the mean-squared displacement associated with the process under study. We use computer simulations to examine the signature of several biologically relevant diffusion processes (simple diffusion, continuous-time random walk, caged diffusion, obstructed diffusion, two-state diffusion, and diffusing diffusivity) in variable-length-scale FCS. We show that, when used in concert, length-scale variation and data inversion permit us to identify non-Gaussian processes and, regardless of Gaussianity, to retrieve their mean-squared displacement over several orders of magnitude in time. This makes unbiased discrimination between different classes of diffusion models possible."],"journal":["Biophysical journal"],"pagination":["791-806"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC6400862"],"repository":["biostudies-literature"],"pubmed_title":["Anomalous Diffusion in Inverted Variable-Lengthscale Fluorescence Correlation Spectroscopy."],"pmcid":["PMC6400862"],"pubmed_authors":["Stolle MDN","Fradin C"],"additional_accession":[]},"is_claimable":false,"name":"Anomalous Diffusion in Inverted Variable-Lengthscale Fluorescence Correlation Spectroscopy.","description":"Using fluorescence correlation spectroscopy (FCS) to distinguish between different types of diffusion processes is often a perilous undertaking because the analysis of the resulting autocorrelation data is model dependant. Two recently introduced strategies, however, can help move toward a model-independent interpretation of FCS experiments: 1) the obtention of correlation data at different length scales and 2) their inversion to retrieve the mean-squared displacement associated with the process under study. We use computer simulations to examine the signature of several biologically relevant diffusion processes (simple diffusion, continuous-time random walk, caged diffusion, obstructed diffusion, two-state diffusion, and diffusing diffusivity) in variable-length-scale FCS. We show that, when used in concert, length-scale variation and data inversion permit us to identify non-Gaussian processes and, regardless of Gaussianity, to retrieve their mean-squared displacement over several orders of magnitude in time. This makes unbiased discrimination between different classes of diffusion models possible.","dates":{"release":"2019-01-01T00:00:00Z","publication":"2019 Mar","modification":"2025-04-22T03:03:20.905Z","creation":"2025-02-19T01:48:07.159Z"},"accession":"S-EPMC6400862","cross_references":{"pubmed":["30782396"],"doi":["10.1016/j.bpj.2019.01.024"]}}