Invention Grant
- Patent Title: Bayesian inference of particle motion and dynamics from single particle tracking and fluorescence correlation spectroscopy
- Patent Title (中): 单粒子跟踪和荧光相关光谱学对粒子运动和动力学的贝叶斯推理
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Application No.: US13328879Application Date: 2011-12-16
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Publication No.: US08542898B2Publication Date: 2013-09-24
- Inventor: Mark Bathe , Jun He , Syuan-Ming Guo , Nilah Monnier
- Applicant: Mark Bathe , Jun He , Syuan-Ming Guo , Nilah Monnier
- Applicant Address: US MA Cambridge
- Assignee: Massachusetts Institute of Technology
- Current Assignee: Massachusetts Institute of Technology
- Current Assignee Address: US MA Cambridge
- Agency: Evans & Molinelli PLLC
- Agent Eugene J. Molinelli
- Main IPC: G06K9/00
- IPC: G06K9/00

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.
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