Hidden Markov modeling of single-particle diffusion with stochastic tethering.
| Autor: | Federbush A; Department of Condensed Matter Physics, Tel Aviv University, Tel Aviv 69978, Israel.; Center for Physics and Chemistry of Living Systems, Tel Aviv University, Tel Aviv 69978, Israel., Moscovich A; Department of Statistics and Operations Research, Tel Aviv University, Tel Aviv 69978, Israel., Bar-Sinai Y; Department of Condensed Matter Physics, Tel Aviv University, Tel Aviv 69978, Israel.; Center for Physics and Chemistry of Living Systems, Tel Aviv University, Tel Aviv 69978, Israel. |
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| Jazyk: | angličtina |
| Zdroj: | Physical review. E [Phys Rev E] 2024 Mar; Vol. 109 (3-1), pp. 034129. |
| DOI: | 10.1103/PhysRevE.109.034129 |
| Abstrakt: | The statistics of the diffusive motion of particles often serve as an experimental proxy for their interaction with the environment. However, inferring the physical properties from the observed trajectories is challenging. Inspired by a recent experiment, here we analyze the problem of particles undergoing two-dimensional Brownian motion with transient tethering to the surface. We model the problem as a hidden Markov model where the physical position is observed and the tethering state is hidden. We develop an alternating maximization algorithm to infer the hidden state of the particle and estimate the physical parameters of the system. The crux of our method is a saddle-point-like approximation, which involves finding the most likely sequence of hidden states and estimating the physical parameters from it. Extensive numerical tests demonstrate that our algorithm reliably finds the model parameters and is insensitive to the initial guess. We discuss the different regimes of physical parameters and the algorithm's performance in these regimes. We also provide a free software implementation of our algorithm. |
| Databáze: | MEDLINE |
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