John Fricks

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  Bridging Scales in Molecular Motor Models: From Diffusing Heads to Multiple Steps
  John Fricks
  A stochastic model for variable-length stepping of kinesins engineered with extended neck linkers is developed. This requires consideration of the separation in microtubule binding sites between the heads of the motor at the beginning of a step. It can be shown that the separation is a stationary Markov process and can be included in the calculation of standard experimental quantities, such as asymptotic velocity and effective diffusion, through the appropriate limits of a semi-Markov process. Using this framework, asymptotic results for randomly detached motors are also obtained and linked to the statistical analysis of velocity data from motor assays. In addition, we will discuss how the framework developed here could be used as one component of a larger scale model for motor-cargo systems of the type to be presented in Kramer's talk.
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  Time Series Analysis of Diffusion with Transient Binding
  John Fricks
  In cellular systems, Brownian forces play a dominant role in the movement of small (and not so small) particles such as vesicles, organelles, etc. However, proteins and other macromolecules bind to one another, altering the underlying Brownian dynamics. In this talk, classical approaches in the biophysical literature to time series which switch between bound and unbound states will be presented, and an alternative approach using stochastic expectation-maximization algorithm (EM) combined with particle filters will be proposed. As an example system, molecular motors, such as kinesin, switch between weakly and strongly bound states, as well as directed transport. I will discuss the analysis of such a system along with the ramifications for multi-motor-cargo complexes found in living cells.