RSMLab : a web-based tool for recombinase-based state machine design and visualization
Name
1017989187-MIT.pdf
Description
Full printable version
Size
1.68 MB
Format
Adobe PDF
Checksum (MD5)
a0434e9bb1b880bf352d374fdb651899
Author(s)
Kugener, Guillaume Georges
Advisor(s)
Timothy K. Lu.
Alternative Title
Web-based tool for recombinase-based state machine design and visualization
Date Issued
2017
Publisher
Massachusetts Institute of Technology
Abstract
Biological 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.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
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 (pages 59-61).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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