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Architecture, Design, and Tradeoffs in Biomolecular Feedback Systems

Citation

Olsman, Noah Andrew (2019) Architecture, Design, and Tradeoffs in Biomolecular Feedback Systems. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/DGPY-1679. http://resolver.caltech.edu/CaltechTHESIS:11262018-100422941

Abstract

A core pursuit in systems and synthetic biology is the analysis of the connection between the low-level structure and parameters of a biomolecular network and its high-level function and performance. Elucidating this mapping has become increasingly feasible as precise measurements of both input parameters and output dynamics become abundant. At the same time, cross-pollination between biology and engineering has led to the realization that many of the mathematical tools from control theory are well-suited to analyze biological processes.

The goal of this thesis is to use tools from control theory to analyze a variety of biomolecular systems from both natural and synthetic settings, and subsequently yield insight into the architecture, tradeoffs, and limitations of biological network. In Chapter 2, I demonstrate how allosteric proteins can be used to respond logarithmically to changes in signal. In Chapter 3, I show how control theoretic techniques can be used to inform the design of synthetic integral feedback networks that implement feedback with a sequestration mechanism. Finally, in Chapter 4 I present a novel simplified model of the E. coli heat shock response system and show how the the mapping of circuit parameters to function depends on the network's architecture.

The unifying theme of this research is that the conceptual framework used to study engineered systems is remarkably well-suited to biology. That being said, it is important to apply these tools in a way that is informed by the molecular details of biological processes. By combining structural and biochemical data with the functional perspective of engineering, it is possible to understand the architectural principles that underlie living systems.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Systems Biology, Synthetic Biology, Control Systems
Degree Grantor:California Institute of Technology
Division:Engineering and Applied Science
Major Option:Control and Dynamical Systems
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Goentoro, Lea A. (co-advisor)
  • Doyle, John C. (co-advisor)
Thesis Committee:
  • Murray, Richard M. (chair)
  • Bois, Justin S.
  • Doyle, John C.
  • Goentoro, Lea A.
Defense Date:16 November 2018
Funders:
Funding AgencyGrant Number
James S. McDonnell Foundation220020365
Defense Advanced Research Projects Agency (DARPA)HR0011-17-2-0008
Record Number:CaltechTHESIS:11262018-100422941
Persistent URL:http://resolver.caltech.edu/CaltechTHESIS:11262018-100422941
DOI:10.7907/DGPY-1679
Related URLs:
URLURL TypeDescription
https://doi.org/10.1073/pnas.1601791113DOIPublished paper associated with Chapter 2.
https://doi.org/10.1101/222042 DOIPreprint of paper associated with Chapter 3.
https://doi.org/10.1101/428300 DOIPreprint of paper associated with Chapter 3.
ORCID:
AuthorORCID
Olsman, Noah Andrew0000-0002-4351-3880
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:11281
Collection:CaltechTHESIS
Deposited By: Noah Olsman
Deposited On:27 Nov 2018 19:30
Last Modified:04 Dec 2018 18:21

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