Bayesian inference of particle motion and dynamics from single particle tracking and fluorescence correlation spectroscopy
US8542898B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 16, 2011 |
| Grant date | Sep 24, 2013 |
| Priority date | — |
| Expiry date | Mar 22, 2032 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30024
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
Techniques for inferring particle dynamics from certain data include determining multiple models for motion of particles in a biological sample. Each model includes a corresponding set of one or more parameters. Measured data is obtained based on measurements at one or more voxels of an imaging system sensitive to motion of particles in the biological sample; and, determining noise correlation of the measured data. Based at least in part on the noise correlation, a marginal likelihood is determined of the measured data given each model of the multiple models. A relative probability for each model is determined based on the marginal likelihood. Based at least in part on the relative probability for each model, a value is determined for at least one parameter of the set of one or more parameters corresponding to a selected model of the multiple models.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.