Synthetic analog feedback control circuits in living cells

Models of biochemical reaction networks in cells are important for advancing our understanding of complex biological systems and for designing functional synthetic biological circuits. However, most models are based on a deterministic digital framework that is largely incompatible with nonlinear dynamics, stochastics, high-order feedback, cross talk, loading, and resource consumption in biology. In contrast, analog circuit design is the nearly 100-year-old art of crafting and analyzing nonlinear, stochastic, coupled differential equations to perform a desired task, often to given speed, precision, input sensitivity, power, load, or part-count constraints and in the presence of noise or device mismatch. In this thesis, we develop a canonical analog circuit that maps a wide class of biological circuits, whether at the DNA, RNA, protein, or small-molecule levels to design schematics that represent their underlying dynamical differential equations exactly.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Computational and Systems Biology Program

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2019

Author dc:creator

• Teo, Jonathan Jin Yuan.

Advisor dc:contributor.advisor

• Rahul Sarpeshkar.

• Computational and Systems Biology Program.

Statement dc:rights

• 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.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/122722

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/122722