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dc.contributor.advisorRon Weiss.en_US
dc.contributor.authorThiagarajan, Arvind, M. Eng. Massachusetts Institute of Technologyen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2019-01-11T15:06:16Z
dc.date.available2019-01-11T15:06:16Z
dc.date.copyright2018en_US
dc.date.issued2018en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/119918
dc.descriptionThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (page 68).en_US
dc.description.abstractEngineering 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.en_US
dc.description.statementofresponsibilityby Arvind Thiagarajan.en_US
dc.format.extent68 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT 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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleModification and sensitivity of equilibria in partially characterized genetic networksen_US
dc.typeThesisen_US
dc.description.degreeM. Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.identifier.oclc1080867296en_US


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