A Caltech Library Service

Modeling Frameworks for Modular and Scalable Biological Circuit Design


Pandey, Ayush (2024) Modeling Frameworks for Modular and Scalable Biological Circuit Design. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/qacp-dw76.


Synthetic biology is a rapidly evolving interdisciplinary field that combines principles from biology, bioengineering, biochemistry, and computational sciences to design and engineer new biological systems for various applications. This thesis focuses on addressing the challenges in engineering large and complex biological circuits. We develop modular modeling frameworks, formal theory, and computer-assisted design (CAD) tools for design and analysis of biological systems at a larger scale.

This thesis introduces a new problem of robustness in structured model reduction of dynamical systems and provides bounds on a robustness distance metric for linear and nonlinear systems. With this theory, we show the discrimination and quantification of different mathematical models, considering resource loading effects in biological circuits.

Using our proposed model reduction robustness theory and its associated software development, we build a modeling, analysis, and parameter identification pipeline. This pipeline is demonstrated through the characterization of DNA recombination enzymes in a cell-free protein expression system. This pipeline is a general approach to systematically develop mathematical models, infer parameters from experimental data, and guide experimental design choices.

Identification of parameters in detailed mathematical models is a major challenge in synthetic biology where only sparse data is available. This prevents the application of our detail-driven modeling approach to larger biological systems. Hence, to address this limitation, we present a formal methods-based approach for specifying and synthesizing implementations for the design of biological circuits. We present a contract-based design framework for synthetic biology. We write formal description of design objectives at a higher level of abstraction without modeling the details of each component. This design framework facilitates the design and prediction of complex synthetic biological circuits at scale.

Overall, this thesis contributes to the advancement of synthetic biology by providing novel modeling frameworks, analysis methods, and design approaches. These contributions aim to enable the design and analysis of complex biological systems and foster the systematic engineering of biological circuits.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:model reduction, synthetic biology, system design
Degree Grantor:California Institute of Technology
Division:Engineering and Applied Science
Major Option:Control and Dynamical Systems
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Murray, Richard M.
Thesis Committee:
  • Doyle, John Comstock (chair)
  • Pierce, Niles A.
  • Del Vecchio, Domitilla
  • Murray, Richard M.
Defense Date:21 June 2023
Non-Caltech Author Email:ayush.9.pandey (AT)
Funding AgencyGrant Number
Air Force Office of Scientific Research (AFOSR)FA9550-22-1-0316
Defense Advanced Research Projects Agency (DARPA)HR0011-17-2-0008
Record Number:CaltechTHESIS:06062023-021337351
Persistent URL:
Related URLs:
URLURL TypeDescription for Ch. 2 for Ch. 3 for Ch. 4 BioSCRAPE (Bio-circuit Stochastic Single-cell Reaction Analysis and Parameter Estimation) Python based automated model reduction tool for SBML models A package for compositional system analysis and design
Pandey, Ayush0000-0003-3590-4459
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:16087
Deposited By: Ayush Pandey
Deposited On:29 Jun 2023 20:53
Last Modified:22 Aug 2023 20:42

Thesis Files

[img] PDF - Final Version
See Usage Policy.


Repository Staff Only: item control page