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Applications of a Distributed Computational Method for Microparticle Tracking in Biological Fluids Lysy, Martin
Description
State-of-the-art techniques in passive particle-tracking microscopy provide high-resolution path trajectories of diverse foreign particles in biological fluids. In order to analyze experiments often tracking thousands of particles at once, scientists must account for many sources of unwanted variability, such as heterogeneity of the fluid environment and measurement error. To this end, this talk presents a versatile family of hierarchical stochastic process models, along with a scalable split-merge distributed computing strategy for parameter inference. Also presented are several applications to quantifying subdiffusive mobility of tracer particles in human lung mucus.
Item Metadata
Title |
Applications of a Distributed Computational Method for Microparticle Tracking in Biological Fluids
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Creator | |
Publisher |
Banff International Research Station for Mathematical Innovation and Discovery
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Date Issued |
2018-05-22T09:00
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Description |
State-of-the-art techniques in passive particle-tracking microscopy provide high-resolution path trajectories of diverse foreign particles in biological fluids. In order to analyze experiments often tracking thousands of particles at once, scientists must account for many sources of unwanted variability, such as heterogeneity of the fluid environment and measurement error. To this end, this talk presents a versatile family of hierarchical stochastic process models, along with a scalable split-merge distributed computing strategy for parameter inference. Also presented are several applications to quantifying subdiffusive mobility of tracer particles in human lung mucus.
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Extent |
44.0
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Subject | |
Type | |
File Format |
video/mp4
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Language |
eng
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Notes |
Author affiliation: University of Waterloo
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Series | |
Date Available |
2019-03-20
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0377201
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URI | |
Affiliation | |
Peer Review Status |
Unreviewed
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Scholarly Level |
Researcher
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International