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June 2008 Stochastic modeling in nanoscale biophysics: Subdiffusion within proteins
S. C. Kou
Ann. Appl. Stat. 2(2): 501-535 (June 2008). DOI: 10.1214/07-AOAS149

Abstract

Advances in nanotechnology have allowed scientists to study biological processes on an unprecedented nanoscale molecule-by-molecule basis, opening the door to addressing many important biological problems. A phenomenon observed in recent nanoscale single-molecule biophysics experiments is subdiffusion, which largely departs from the classical Brownian diffusion theory. In this paper, by incorporating fractional Gaussian noise into the generalized Langevin equation, we formulate a model to describe subdiffusion. We conduct a detailed analysis of the model, including (i) a spectral analysis of the stochastic integro-differential equations introduced in the model and (ii) a microscopic derivation of the model from a system of interacting particles. In addition to its analytical tractability and clear physical underpinning, the model is capable of explaining data collected in fluorescence studies on single protein molecules. Excellent agreement between the model prediction and the single-molecule experimental data is seen.

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S. C. Kou. "Stochastic modeling in nanoscale biophysics: Subdiffusion within proteins." Ann. Appl. Stat. 2 (2) 501 - 535, June 2008. https://doi.org/10.1214/07-AOAS149

Information

Published: June 2008
First available in Project Euclid: 3 July 2008

zbMATH: 05591286
MathSciNet: MR2524344
Digital Object Identifier: 10.1214/07-AOAS149

Keywords: autocorrelation function , Fourier transform , fractional Brownian motion , generalized Langevin equation , Hamiltonian , harmonic potential , memory kernel

Rights: Copyright © 2008 Institute of Mathematical Statistics

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Vol.2 • No. 2 • June 2008
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