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The Signal in the Noise: Developing Tools to Extract Meaning from Biological Variation.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	The Signal in the Noise: Developing Tools to Extract Meaning from Biological Variation./
作者:	Miller, Cayla Marie.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	105 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-09, Section: B.
Contained By:	Dissertations Abstracts International83-09B.
標題:	Cameras. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29003865
ISBN:	9798209787822

The Signal in the Noise: Developing Tools to Extract Meaning from Biological Variation.
Miller, Cayla Marie.

The Signal in the Noise: Developing Tools to Extract Meaning from Biological Variation. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 105 p.

Source: Dissertations Abstracts International, Volume: 83-09, Section: B.

Thesis (Ph.D.)--Stanford University, 2021.

This item must not be sold to any third party vendors.

Mammalian cells contain a multitude of dynamic structures, from those of force-generating cytoskeletal fibers to the networks of ATP-producing mitochondria. While the structure and dynamics of these systems have been made visible by advances in microscopy, the quantification of useful metrics from these images still requires careful and tailored analysis. Here, I present my work developing statistical tools and analysis pipelines in order to elucidate biological properties and mechanism in three studies: (1) the accurate measurement of cytoskeletal actin velocity distributions, (2) the characterization of mitochondria network topology, and (3) the development of quantitative tools to describe focal adhesion ultrastructure.In the first, I developed a statistical approach to accurately estimate F-actin velocity distributions in living cells. Filamentous or F-actin is a cytoskeletal polymer that provides cellular structure and facilitates cellular movement. These structures are dynamic and assemble and disassemble on the timescale of tens of seconds to minutes and move on the scale of single to tens of nanometers per second. In this study, I examined whether F-actin motion is best described by continuous, diffusive motion, or by discontinuous motion, here described by a jump process. In order to accurately measure F-actin displacements to distinguish between these models, I developed a Bayesian fitting procedure to extract estimated true velocity distributions from noise-limited measurements. I found that the measured F-actin velocities were more consistent with jump-like motion, where individual filaments undergo sudden, rapid movements followed by periods of stillness.In the second, I quantitatively characterized the 3-D topology of mitochondria networks in fibroblasts. Mitochondria produce ATP, the energy currency of the cell, and thus their positioning in the cell is critical to be able to meet local energy needs to complete cellular functions. The topology of this network has likewise been linked to cell state. While we know that mitochondria are transported along microtubules, and that this interaction is required for many cellular processes, it is still unclear how the microtubule network may help to pattern and maintain mitochondria network topology. We therefore developed methods to characterize the mitochondria network in 3D and examined the effects of microtubule perturbations on the mitochondria network properties. I found that an intact microtubule network could facilitate a well-connected and well-spread mitochondria network and was necessary for the spatial patterning of mitochondria network features.Lastly, I generated a suite of quantitative metrics to describe the organization of protein clusters within focal adhesions. These large protein complexes can contain hundreds of proteins and are critical for cell adhesion and migration. How the cell organizes these many components into a functional unit is unclear, though many works have shown the formation of protein clusters within the focal adhesion. Here, I developed methods to examine the relationships between localizations of protein A-protein B pairs and A-B-C triples. By quantifying these pair- and triple-wise spatial interactions, we can begin to build up logical rules by which the cell organizes proteins within these complexes.Taken together, these studies illustrate both the rich biological data which can be extracted from microscopy experiments and the development of quantitative tools which may be useful in the characterization of other cellular structures and processes.

ISBN: 9798209787822Subjects--Topical Terms:

524039
Cameras.

The Signal in the Noise: Developing Tools to Extract Meaning from Biological Variation.
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502 $a Thesis (Ph.D.)--Stanford University, 2021.
506 $a This item must not be sold to any third party vendors.
520 $a Mammalian cells contain a multitude of dynamic structures, from those of force-generating cytoskeletal fibers to the networks of ATP-producing mitochondria. While the structure and dynamics of these systems have been made visible by advances in microscopy, the quantification of useful metrics from these images still requires careful and tailored analysis. Here, I present my work developing statistical tools and analysis pipelines in order to elucidate biological properties and mechanism in three studies: (1) the accurate measurement of cytoskeletal actin velocity distributions, (2) the characterization of mitochondria network topology, and (3) the development of quantitative tools to describe focal adhesion ultrastructure.In the first, I developed a statistical approach to accurately estimate F-actin velocity distributions in living cells. Filamentous or F-actin is a cytoskeletal polymer that provides cellular structure and facilitates cellular movement. These structures are dynamic and assemble and disassemble on the timescale of tens of seconds to minutes and move on the scale of single to tens of nanometers per second. In this study, I examined whether F-actin motion is best described by continuous, diffusive motion, or by discontinuous motion, here described by a jump process. In order to accurately measure F-actin displacements to distinguish between these models, I developed a Bayesian fitting procedure to extract estimated true velocity distributions from noise-limited measurements. I found that the measured F-actin velocities were more consistent with jump-like motion, where individual filaments undergo sudden, rapid movements followed by periods of stillness.In the second, I quantitatively characterized the 3-D topology of mitochondria networks in fibroblasts. Mitochondria produce ATP, the energy currency of the cell, and thus their positioning in the cell is critical to be able to meet local energy needs to complete cellular functions. The topology of this network has likewise been linked to cell state. While we know that mitochondria are transported along microtubules, and that this interaction is required for many cellular processes, it is still unclear how the microtubule network may help to pattern and maintain mitochondria network topology. We therefore developed methods to characterize the mitochondria network in 3D and examined the effects of microtubule perturbations on the mitochondria network properties. I found that an intact microtubule network could facilitate a well-connected and well-spread mitochondria network and was necessary for the spatial patterning of mitochondria network features.Lastly, I generated a suite of quantitative metrics to describe the organization of protein clusters within focal adhesions. These large protein complexes can contain hundreds of proteins and are critical for cell adhesion and migration. How the cell organizes these many components into a functional unit is unclear, though many works have shown the formation of protein clusters within the focal adhesion. Here, I developed methods to examine the relationships between localizations of protein A-protein B pairs and A-B-C triples. By quantifying these pair- and triple-wise spatial interactions, we can begin to build up logical rules by which the cell organizes proteins within these complexes.Taken together, these studies illustrate both the rich biological data which can be extracted from microscopy experiments and the development of quantitative tools which may be useful in the characterization of other cellular structures and processes.
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