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Recent Advances in Single-Particle Tracking: Experiment and Analysis

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...

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Gardado en:
Formato: Online
Idioma:inglés
Publicado: MDPI - Multidisciplinary Digital Publishing Institute 2022
Subjects:
diauxic 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
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
thema EDItEUR::P Mathematics and Science::PH Physics
Acceso en liña:ONIX_20220506_9783036534855_282
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Summary: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.

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