Full metadata
Title
Advancing Biophysics Research with Bayesian Methods: Novel Applications and Insights into Biological Systems' Behavior
Description
The Bayesian paradigm provides a flexible and versatile framework for modeling complex biological systems without assuming a fixed functional form or other constraints on the underlying data. This dissertation explores the use of Bayesian nonparametric methods for analyzing fluorescence microscopy data in biophysics, with a focus on enumerating diffraction-limited particles, reconstructing potentials from trajectories corrupted by measurement noise, and inferring potential energy landscapes from fluorescence intensity experiments. This research demonstrates the power and potential of Bayesian methods for solving a variety of problems in fluorescence microscopy and biophysics more broadly.
Date Created
2023
Contributors
- Bryan IV, J Shepard (Author)
- Presse, Steve (Thesis advisor)
- Ozkan, Banu (Committee member)
- Wadhwa, Navish (Committee member)
- Shepherd, Doug (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
152 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.2.N.187432
Level of coding
minimal
Cataloging Standards
Note
Partial requirement for: Ph.D., Arizona State University, 2023
Field of study: Physics
System Created
- 2023-06-06 07:37:46
System Modified
- 2023-06-06 07:37:50
- 1 year 5 months ago
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