These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

101 related articles for article (PubMed ID: 31108610)

  • 1. Statistical testing approach for fractional anomalous diffusion classification.
    Weron A; Janczura J; Boryczka E; Sungkaworn T; Calebiro D
    Phys Rev E; 2019 Apr; 99(4-1):042149. PubMed ID: 31108610
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Classification of particle trajectories in living cells: Machine learning versus statistical testing hypothesis for fractional anomalous diffusion.
    Janczura J; Kowalek P; Loch-Olszewska H; Szwabiński J; Weron A
    Phys Rev E; 2020 Sep; 102(3-1):032402. PubMed ID: 33076015
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Anomalous diffusion models and their properties: non-stationarity, non-ergodicity, and ageing at the centenary of single particle tracking.
    Metzler R; Jeon JH; Cherstvy AG; Barkai E
    Phys Chem Chem Phys; 2014 Nov; 16(44):24128-64. PubMed ID: 25297814
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Mean-squared-displacement statistical test for fractional Brownian motion.
    Sikora G; Burnecki K; Wyłomańska A
    Phys Rev E; 2017 Mar; 95(3-1):032110. PubMed ID: 28415337
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Measuring a diffusion coefficient by single-particle tracking: statistical analysis of experimental mean squared displacement curves.
    Ernst D; Köhler J
    Phys Chem Chem Phys; 2013 Jan; 15(3):845-9. PubMed ID: 23202416
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Time-dependent classification of protein diffusion types: A statistical detection of mean-squared-displacement exponent transitions.
    Hubicka K; Janczura J
    Phys Rev E; 2020 Feb; 101(2-1):022107. PubMed ID: 32168604
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Single particle tracking in systems showing anomalous diffusion: the role of weak ergodicity breaking.
    Burov S; Jeon JH; Metzler R; Barkai E
    Phys Chem Chem Phys; 2011 Feb; 13(5):1800-12. PubMed ID: 21203639
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Ergodicity testing for anomalous diffusion: small sample statistics.
    Janczura J; Weron A
    J Chem Phys; 2015 Apr; 142(14):144103. PubMed ID: 25877558
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Estimating the anomalous diffusion exponent for single particle tracking data with measurement errors - An alternative approach.
    Burnecki K; Kepten E; Garini Y; Sikora G; Weron A
    Sci Rep; 2015 Jun; 5():11306. PubMed ID: 26065707
    [TBL] [Abstract][Full Text] [Related]  

  • 10. An efficient algorithm for extracting the magnitude of the measurement error for fractional dynamics.
    Sikora G; Kepten E; Weron A; Balcerek M; Burnecki K
    Phys Chem Chem Phys; 2017 Oct; 19(39):26566-26581. PubMed ID: 28920611
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Nonergodicity mimics inhomogeneity in single particle tracking.
    Lubelski A; Sokolov IM; Klafter J
    Phys Rev Lett; 2008 Jun; 100(25):250602. PubMed ID: 18643647
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Single particle tracking of complex diffusion in membranes: simulation and detection of barrier, raft, and interaction phenomena.
    Jin S; Verkman AS
    J Phys Chem B; 2007 Apr; 111(14):3625-32. PubMed ID: 17388520
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Improved estimation of anomalous diffusion exponents in single-particle tracking experiments.
    Kepten E; Bronshtein I; Garini Y
    Phys Rev E Stat Nonlin Soft Matter Phys; 2013 May; 87(5):052713. PubMed ID: 23767572
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Statistical properties of the anomalous scaling exponent estimator based on time-averaged mean-square displacement.
    Sikora G; Teuerle M; Wyłomańska A; Grebenkov D
    Phys Rev E; 2017 Aug; 96(2-1):022132. PubMed ID: 28950534
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Mechanisms underlying anomalous diffusion in the plasma membrane.
    Krapf D
    Curr Top Membr; 2015; 75():167-207. PubMed ID: 26015283
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Geometry controlled anomalous diffusion in random fractal geometries: looking beyond the infinite cluster.
    Mardoukhi Y; Jeon JH; Metzler R
    Phys Chem Chem Phys; 2015 Nov; 17(44):30134-47. PubMed ID: 26503611
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Statistical analysis of particle trajectories in living cells.
    Briane V; Kervrann C; Vimond M
    Phys Rev E; 2018 Jun; 97(6-1):062121. PubMed ID: 30011544
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Revealing nonergodic dynamics in living cells from a single particle trajectory.
    Lanoiselée Y; Grebenkov DS
    Phys Rev E; 2016 May; 93(5):052146. PubMed ID: 27300868
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Bayesian analysis of single-particle tracking data using the nested-sampling algorithm: maximum-likelihood model selection applied to stochastic-diffusivity data.
    Thapa S; Lomholt MA; Krog J; Cherstvy AG; Metzler R
    Phys Chem Chem Phys; 2018 Nov; 20(46):29018-29037. PubMed ID: 30255886
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A novel computational framework for D(t) from Fluorescence Recovery after Photobleaching data reveals various anomalous diffusion types in live cell membranes.
    Kang M; Day CA; Kenworthy AK
    Traffic; 2019 Nov; 20(11):867-880. PubMed ID: 31452286
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.