Dividing organelle tracks into Brownian and motor-driven intervals by variational maximization of the Bayesian evidence.

ABSTRACT: Many organelles and vesicles in live cells move in a start-stop manner when observed for ~10 s by optical microscopy. Changes in velocity and directional persistence of such particles are a potentially rich source of insight into the mechanisms leading to the start and stop states. Unbiased assessment of the most probable number of states, the properties of each state, and the most probable state for the particle at each moment can be accomplished by variational Bayesian methods combined with a hidden Markov model and a Gaussian mixture model. Our track analysis method, "vbTRACK", applied this combination of methods to particle velocity v or changes in the direction of travel evaluated from simulated tracks and from tracks of peroxisomes in live cells. When tested with numerical data, vbTR

SUBMITTER: Martin MJ 

PROVIDER: S-EPMC5125805 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature