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Plos Computational Biology : a Hidden Markov Model for Single Particle Tracks Quantifies Dynamic Interactions Between Lfa-1 and the Actin Cytoskeleton, Volume 5

By Das, Raibatak

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Book Id: WPLBN0003927187
Format Type: PDF eBook :
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Reproduction Date: 2015

Title: Plos Computational Biology : a Hidden Markov Model for Single Particle Tracks Quantifies Dynamic Interactions Between Lfa-1 and the Actin Cytoskeleton, Volume 5  
Author: Das, Raibatak
Volume: Volume 5
Language: English
Subject: Journals, Science, Computational Biology
Collections: Periodicals: Journal and Magazine Collection (Contemporary), PLoS Computational Biology
Historic
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Publisher: Plos

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Das, R. (n.d.). Plos Computational Biology : a Hidden Markov Model for Single Particle Tracks Quantifies Dynamic Interactions Between Lfa-1 and the Actin Cytoskeleton, Volume 5. Retrieved from http://www.nationalpubliclibrary.info/


Description
Description : The extraction of hidden information from complex trajectories is a continuing problem in single-particle and single-molecule experiments. Particle trajectories are the result of multiple phenomena, and new methods for revealing changes in molecular processes are needed. We have developed a practical technique that is capable of identifying multiple states of diffusion within experimental trajectories. We model single particle tracks for a membrane-associated protein interacting with a homogeneously distributed binding partner and show that, with certain simplifying assumptions, particle trajectories can be regarded as the outcome of a two-state hidden Markov model. Using simulated trajectories, we demonstrate that this model can be used to identify the key biophysical parameters for such a system, namely the diffusion coefficients of the underlying states, and the rates of transition between them. We use a stochastic optimization scheme to compute maximum likelihood estimates of these parameters. We have applied this analysis to single-particle trajectories of the integrin receptor lymphocyte function-associated antigen-1 (LFA-1) on live T cells. Our analysis reveals that the diffusion of LFA-1 is indeed approximately two-state, and is characterized by large changes in cytoskeletal interactions upon cellular activation.

 

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