Modelling non-Markovian fluctuations in intracellular biomolecular transport

Modelling non-Markovian fluctuations in intracellular biomolecular transport •Using Hida stochastic functional integrals, the Probability Density Function of a sinusoidally modulated Brownian motion with memory is solved exactly. This stochastic process is used to model fluctuating values of the diffusion coefficients for proteins of varying lengths.•Comparison of theoretical and empirical Mean Square Deviation (MSD) shows a good match even for a large number of amino acids where nonlinear MSD plots exhibit superdiffusive then subdiffusive behavior.•The theoretical Probability Density Function captures the general behavior of the empirical probability distribution for proteins of increasing length. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Mathematical Biosciences Elsevier

Modelling non-Markovian fluctuations in intracellular biomolecular transport

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Publisher
Elsevier
Copyright
Copyright © 2018 Elsevier Inc.
ISSN
0025-5564
D.O.I.
10.1016/j.mbs.2018.01.004
Publisher site
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Abstract

•Using Hida stochastic functional integrals, the Probability Density Function of a sinusoidally modulated Brownian motion with memory is solved exactly. This stochastic process is used to model fluctuating values of the diffusion coefficients for proteins of varying lengths.•Comparison of theoretical and empirical Mean Square Deviation (MSD) shows a good match even for a large number of amino acids where nonlinear MSD plots exhibit superdiffusive then subdiffusive behavior.•The theoretical Probability Density Function captures the general behavior of the empirical probability distribution for proteins of increasing length.

Journal

Mathematical BiosciencesElsevier

Published: Mar 1, 2018

References

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