PhD Thesis Defense: Douglas Beahm

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Meeting ID: 981 1878 3645
Passcode: 219869

"Modeling biological systems via analog circuits and ordinary differential equations"

Abstract

A tremendous number of quantitative measurements have been made on biological systems, contributing to a massive body of knowledge about how living things work. Yet, we are scarcely able to quantitatively predict the behavior of whole biological systems from the measures of their constituent parts. Furthermore, current technologies cannot directly measure many biological quantities of interest. To aid in addressing these gaps, we contribute dynamical models of biological systems presented interchangeably as analog electrical circuits – suitable for analog computing – and systems of ordinary differential equations (ODEs) – suitable for traditional digital computing. Specifically, we develop a model of SARS-CoV-2 infection that fits biological data and explains the effects of age, sex, viral variant, and treatment type on infection dynamics. Then, we present a more general model of immune-pathogen interaction in which we visualize parameter-outcome relationship landscapes. Assuming that adequate circuit/ODE models of disease and treatment can be obtained, we demonstrate an application of Dijkstra’s algorithm that selects the optimal dose amounts, dose schedules, and drug combinations for treatment regimen design. In the direction of generating new biological knowledge in conjunction with wet lab experiments, we create a model of E. coli ATP metabolism that fits experimental data to infer ATP production and consumption rates across growth stages. Additionally, we fit a novel model of antibiotic persister cell dynamics to biphasic killing curve data from antibiotic-treated E. coli cultures in order to measure the antibiotic-induced persister formation rate. Taken in its entirety, our work demonstrates the many ways in which analog circuit and ODE models can be used to make predictions about, and take measurements of, biological systems.

Thesis Committee

• Rahul Sarpeshkar (chair)
• Margaret Ackerman
• Daniel Schultz
• Edward Stites (Yale University)

Contact

For more information, contact Thayer Registrar at thayer.registrar@dartmouth.edu .