Hidden Markov model analysis of motor protein data

Brian Walton
Washington State University

Recent biophysical experiments have tethered a glass bead to an
individual kinesin which allows one to impose an external force by
laser tweezers as well as to record detailed position measurements of
the bead as it moves. We model the experimental system with a Markov
chain for the protein and with a Brownian motion in a quadratic
potential for the glass bead. Such a model facilitates the use of
hidden Markov models to analyze experimental data. I will formulate the
methodology of hidden Markov models and give examples of how it can
provide a statistical framework to ask questions about particular
models.

Presentation (PDF File)

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