The Annals of Applied Statistics

Stochastic modeling in nanoscale biophysics: Subdiffusion within proteins

S. C. Kou

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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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Ann. Appl. Stat., Volume 2, Number 2 (2008), 501-535.

First available in Project Euclid: 3 July 2008

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Fractional Brownian motion generalized Langevin equation Fourier transform autocorrelation function memory kernel harmonic potential Hamiltonian


Kou, S. C. Stochastic modeling in nanoscale biophysics: Subdiffusion within proteins. Ann. Appl. Stat. 2 (2008), no. 2, 501--535. doi:10.1214/07-AOAS149.

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