Abstract
Live-cell imaging and particle tracking provide rich information on mechanisms of intracellular transport. However, trajectory analysis procedures to infer complex transport dynamics involving stochastic switching between active transport and diffusive motion are lacking. We applied Bayesian model selection to hidden Markov modeling to infer transient transport states from trajectories of mRNA-protein complexes in live mouse hippocampal neurons and metaphase kinetochores in dividing human cells. The software is available at http://hmm-bayes.org/.
Publication types
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Research Support, N.I.H., Extramural
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Research Support, Non-U.S. Gov't
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Research Support, U.S. Gov't, Non-P.H.S.
MeSH terms
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Actins / metabolism*
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Animals
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Bayes Theorem
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Cells, Cultured
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Computer Simulation
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Female
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HeLa Cells
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Hippocampus / cytology
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Hippocampus / metabolism*
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Humans
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Markov Chains
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Mice
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MicroRNAs / metabolism
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Microscopy, Fluorescence / methods
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Models, Biological*
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Models, Statistical
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Molecular Imaging / methods*
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Neurons / cytology*
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Neurons / metabolism*
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Pattern Recognition, Automated / methods
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Protein Transport / physiology
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Software