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Abstract:
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Various biophysical processes exhibit switching between free and bound diffusive regimes. For example, a particle, such as a protein, may freely diffuse through the cell membrane until it hits a binding site, where it will remain bound until detaching and resuming free diffusion. Experimentalists characterize such processes through the regime transition rates, diffusion coefficients, and the forces acting on the particle when bound. In this talk, I model diffusion with transient binding as Markov switching between free Brownian diffusion and an overdamped Langevin equation in the bound regime, where the potential function is represented as additive. The unobserved regime of the particle and binding site locations are predicted with an infill-based particle filter and model parameters are estimated with a stochastic EM algorithm. Smoothness of the estimated potential function is imposed by taking a penalized likelihood approach.
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