How to connect time-lapse recorded trajectories of motile microorganisms with dynamical models in continuous time
Year: 2016
Type: article
Abstract: We provide a tool for data-driven modeling of motility, data being time-lapse recorded trajectories. Several mathematical properties of a model to be found can be gleaned from appropriate model-independent experimental statistics, if one understands how such statistics are distorted by the finite sampling frequency of time-lapse recording, by experimental errors on recorded positions, and by conditional averaging. We give exact analytical expressions for these effects in the simplest possible model for persistent random motion, the Ornstein-Uhlenbeck process. Then we describe those aspects of these effects that are valid for any reasonable model for persistent random motion. Our findings are illustrated with experimental data and Monte Carlo simulations.
Source: Physical review. E
Authors: Jonas N. Pedersen, Liang Li, Cristian Grădinaru, Robert H. Austin, Edward C. Cox, Henrik Flyvbjerg
Institutions: Technical University of Denmark, Princeton University
Language: English
Topic: Micro and Nano Robotics
Subfield: Condensed Matter Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: bronze
Awards: G155546615, G2737604797, G2973790809, G3207356259, G393177772, G4152390927, High Throughput Systematic Single Cell Genomics using Micro/Nano-Fluidic Chips for Extracting, Pre-analysing, Selecting and Preparing Sequence-ready DNA, G5702163051, CAAX Processing and Cell Signaling in Dictyostelium, Understanding interactions between cells and nanopatterned surfaces, G9000290534
OpenAlex ID: W2560220759