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dc.contributor.advisorTimothy K. Lu.en_US
dc.contributor.authorKugener, Guillaume Georgesen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2018-01-12T20:58:58Z
dc.date.available2018-01-12T20:58:58Z
dc.date.copyright2017en_US
dc.date.issued2017en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/113138
dc.descriptionThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.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 (pages 59-61).en_US
dc.description.abstractBiological state machines have the potential to enable a wide range of applications but until recently have been challenging to implement experimentally. To overcome this challenge, we described a scalable strategy for assembling biological state machines using recombinases. This platform enables the implementation of biological state machines with arbitrary behaviors, but the manual design of such state machines is increasingly challenging with increasing complexities. Here, we introduce RSMLab, an intuitive web-based application for creating circuits that implement state-dependent logic in living cells using our scalable state-machine framework. Through a graphical user interface, RSMLab users choose a desired state diagram, define arbitrary genes, and specify whether those genes are on or off in each state. RSMLab then returns a visualization of possible gene circuits that correspond to the user specifications. We use the RSMLab algorithm and demonstrate the circuit design process using examples of two-input, five-state and three-input, sixteen-state gene regulation programs. With the help of RSMLab, researchers can program state-dependent logic to study and program the way that cells respond to combinational and temporally distributed chemical events, without needing to be expert gene circuit engineers. We envision that biology-focused design software such as RSMLab will enable the faster, more reliable, and more accessible creation of DNA-encoded circuits for engineering complex cellular behaviors.en_US
dc.description.statementofresponsibilityby Guillaume Georges Kugener.en_US
dc.format.extent61 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.titleRSMLab : a web-based tool for recombinase-based state machine design and visualizationen_US
dc.title.alternativeWeb-based tool for recombinase-based state machine design and visualizationen_US
dc.typeThesisen_US
dc.description.degreeM. Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc1017989187en_US


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