Recent Advances in Single-Particle Tracking: Experiment and Analysis
Szwabiński, Janusz (editor)
Weron, Aleksander (editor)
This Special Issue of Entropy, titled “Recent Advances in Single-Particle Tracking: Experiment and Analysis”, contains a collection of 13 papers concerning different aspects of single-particle tracking, a popular experimental technique that has deeply penetrated molecular biology and statistical and chemical physics. Presenting original research, yet written in an accessible style, this collection will be useful for both newcomers to the field and more experienced researchers looking for some reference. Several papers are written by authorities in the field, and the topics cover aspects of experimental setups, analytical methods of tracking data analysis, a machine learning approach to data and, finally, some more general issues related to diffusion.
Keywordsdiauxic growth; replicator equation; mesoscopic model; integro-differential equations; anomalous diffusion; statistical analysis; single-particle tracking; trajectory classification; fractional Brownian motion; estimation; autocovariance function; neural network; Monte Carlo simulations; multifractional Brownian motion; power of the statistical test; machine learning classification; feature engineering; confinement; information theory; Brownian particle; stochastic thermodynamics; CTRW; diffusing-diffusivity; occupation time statistics; wound healing dynamics; single pseudo-particle tracking; phase contrast image segmentation; 3D single-particle tracking; Fisher information; non-uniform illumination; SPT; deep learning; residual neural networks; random walk; heterogeneous; endosomes; single particle trajectory; stochastic processes; trapping
Webshop linkhttps://mdpi.com/books/pdfview ...
Publication date and placeBasel, 2022
Research & information: general