Modification and sensitivity of equilibria in partially characterized genetic networks

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.

Bibliographic Details
Main Author: Thiagarajan, Arvind, M. Eng. Massachusetts Institute of Technology
Other Authors: Ron Weiss.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2019
Subjects:
Online Access:http://hdl.handle.net/1721.1/119918
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author Thiagarajan, Arvind, M. Eng. Massachusetts Institute of Technology
author2 Ron Weiss.
author_facet Ron Weiss.
Thiagarajan, Arvind, M. Eng. Massachusetts Institute of Technology
author_sort Thiagarajan, Arvind, M. Eng. Massachusetts Institute of Technology
collection MIT
description Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
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spelling mit-1721.1/1199182019-04-10T13:24:24Z Modification and sensitivity of equilibria in partially characterized genetic networks Thiagarajan, Arvind, M. Eng. Massachusetts Institute of Technology Ron Weiss. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (page 68). Engineering intracellular biological control systems, whether to perform artificial functions or to modify existing behavior, requires accurate characterization of genetic networks. Slight errors in characterization lead to significant changes in predicted behavior, and consequently to design errors that are difficult to debug. Metabolic engineering provides an empirical solution to this problem by varying many system parameters simultaneously to optimize the steady state level of a particular chemical species. Such approaches, though effective, require significant customization for the systems being studied. Here I propose and investigate, in silico via generation and analysis of random genetic networks, a more general approach in which a small number of modifications, selected empirically, are made to genetic networks. We found that feedback loop based modifications were most effective, and that responses to modifications depended significantly on network structure. Our work serves to advance a potential technique for efficient empirical design and modification of genetic networks. by Arvind Thiagarajan. M. Eng. 2019-01-11T15:06:16Z 2019-01-11T15:06:16Z 2018 2018 Thesis http://hdl.handle.net/1721.1/119918 1080867296 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 68 pages application/pdf Massachusetts Institute of Technology
spellingShingle Electrical Engineering and Computer Science.
Thiagarajan, Arvind, M. Eng. Massachusetts Institute of Technology
Modification and sensitivity of equilibria in partially characterized genetic networks
title Modification and sensitivity of equilibria in partially characterized genetic networks
title_full Modification and sensitivity of equilibria in partially characterized genetic networks
title_fullStr Modification and sensitivity of equilibria in partially characterized genetic networks
title_full_unstemmed Modification and sensitivity of equilibria in partially characterized genetic networks
title_short Modification and sensitivity of equilibria in partially characterized genetic networks
title_sort modification and sensitivity of equilibria in partially characterized genetic networks
topic Electrical Engineering and Computer Science.
url http://hdl.handle.net/1721.1/119918
work_keys_str_mv AT thiagarajanarvindmengmassachusettsinstituteoftechnology modificationandsensitivityofequilibriainpartiallycharacterizedgeneticnetworks