2026-09-20T12:30:14Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1302162026-06-16T18:54:50Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
Nikta Fakhri.
Jung, Yoon,Ph. D.Massachusetts Institute of Technology.
Massachusetts Institute of Technology. Department of Physics.
Massachusetts Institute of Technology. Department of Physics
2021-03-22T17:35:36Z
2021-03-22T17:35:36Z
2020
2020
https://hdl.handle.net/1721.1/130216
1241733258
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Physics, May, 2020
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 63-70).
Biological systems are far from equilibrium which require novel tools for unraveling their complex behavior. This thesis focuses on developing a toolbox in order to understand properties of living systems from thermodynamic fluctuations. In the first chapter, I discuss a fluorescence imaging platform which allows 3D information combined with non-invasive and photostable probes named single-walled carbon nanotubes. The second chapter discusses an image processing algorithm for analyzing the fluorescence images acquired with the proposed custom-built microscope. I demonstrate its robust image reconstruction capability under dense scenes of fluorescence images with its inherent parallel nature which allows implementation on GPUs. Finally, I develop a framework which predicts system properties from thermodynamic fluctuations in a data-driven manner. The proposed framework uses feature extraction methods based on wavelets with recurrent neural networks for processing time series data. A combination of these tools completes a pipeline which allows studying complex behavior of biological systems.
by Yoon Jung.
Ph.D.
Ph.D. Massachusetts Institute of Technology, Department of Physics
70 pages
eng
Massachusetts Institute of Technology
MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
http://dspace.mit.edu/handle/1721.1/7582
Physics.
Inferring system properties from thermodynamic fluctuations : a tool development approach
Thesis
application/pdf
2021-03-22T17:34:57Z
Publication
Doctoral
Phys
unknown
unknown
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<Abstract>Biological systems are far from equilibrium which require novel tools for unraveling their complex behavior. This thesis focuses on developing a toolbox in order to understand properties of living systems from thermodynamic fluctuations. In the first chapter, I discuss a fluorescence imaging platform which allows 3D information combined with non-invasive and photostable probes named single-walled carbon nanotubes. The second chapter discusses an image processing algorithm for analyzing the fluorescence images acquired with the proposed custom-built microscope. I demonstrate its robust image reconstruction capability under dense scenes of fluorescence images with its inherent parallel nature which allows implementation on GPUs. Finally, I develop a framework which predicts system properties from thermodynamic fluctuations in a data-driven manner. The proposed framework uses feature extraction methods based on wavelets with recurrent neural networks for processing time series data. A combination of these tools completes a pipeline which allows studying complex behavior of biological systems.</Abstract>
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