Literature DB >> 32168604

Time-dependent classification of protein diffusion types: A statistical detection of mean-squared-displacement exponent transitions.

Katarzyna Hubicka1, Joanna Janczura1.   

Abstract

In this paper, we have proposed a statistical procedure for detecting transitions of the mean-square-displacement exponent value within a single trajectory. With this procedure, we have identified three regimes of proteins dynamics on a cell membrane, namely, subdiffusion, free diffusion, and immobility. The fourth considered dynamics type, namely, superdiffusion was not detected. We show that the analyzed protein trajectories are not stationary and not ergodic. Moreover, classification of the dynamics type performed without prior detection of transitions may lead to the overestimation of the proportion of subdiffusive trajectories.

Mesh:

Substances:

Year:  2020        PMID: 32168604     DOI: 10.1103/PhysRevE.101.022107

Source DB:  PubMed          Journal:  Phys Rev E        ISSN: 2470-0045            Impact factor:   2.529


  3 in total

1.  Impact of Feature Choice on Machine Learning Classification of Fractional Anomalous Diffusion.

Authors:  Hanna Loch-Olszewska; Janusz Szwabiński
Journal:  Entropy (Basel)       Date:  2020-12-19       Impact factor: 2.524

2.  Fundamentals of the logarithmic measure for revealing multimodal diffusion.

Authors:  Benjamin A Dalton; Ivo F Sbalzarini; Itsuo Hanasaki
Journal:  Biophys J       Date:  2021-01-14       Impact factor: 4.033

3.  An Estimation Algorithm for General Linear Single Particle Tracking Models with Time-Varying Parameters.

Authors:  Boris I Godoy; Nicholas A Vickers; Sean B Andersson
Journal:  Molecules       Date:  2021-02-08       Impact factor: 4.411

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.