Multi-state Diffusion Analysis with Measurement Errors
Date:
Talk on “Reverse mathematical methods for reconstructing molecular dynamics in single cell”.
Abstract: Single particle tracking is a powerful tool to study the mobility of molecules in the cell membrane.The most common approaches in analyzing these kinds of data are mean square displacement and analyses with one or more hidden Markov states. However, in most experiments, positional measurements contain systematic and random errors, and to achieve proper fits, we must take these errors into account. In this work, we develop a hidden Markov model with multiple diffusive states. Our goal is to estimate the diffusion coefficients and transition probabilities between the different states, incorporating uncertainty due to measurement error in a rational way. We test our methods using simulated data and present results using particle tracks obtained from surface receptor molecules on B cells.