Computational Biology Thesis Defense

  • Remote Access Enabled - Zoom
  • Virtual Presentation
  • MARCUS THOMAS
  • Ph.D. Student
  • Joint CMU-Pitt Ph.D. Program in Computational Biology
  • Computational Biology Department, Carnegie Mellon University
Thesis Orals

Macromolecular Self-Assembly: Simulation and Optimization

This thesis describes computational methods for the investigation of macromolecular self-assembly as well as methods for the simulation of general reaction-diffusion chemistry. I will briefly motivate the choice of model system, viral capsid assembly, and discuss my contribution, which is a pipeline for the inference of kinetic rate parameters governing assembly pathways. This includes a new black-box parameter optimization methodology suitable for noisy objective values, and using multiple Gaussian processes. Next, I will discuss the landscape of course-grained simulation methods for reaction-diffusion chemistry and their limitations. I will present a novel algorithm generalizing the stochastic simulation algorithm (SSA) to an explicit 3d space and describe its physical justification as well as its improvements over the state of the art in certain respects, e.g. run time efficiency. The algorithm extends the non-spatial SSA approach in two major ways. First, bimolecular association reactions are sampled following diffusive motion using time-dependent reaction propensities. Second, reaction locations are sampled from within overlapping diffusion spheres describing the spatial probability densities of individual reactants. The approach provides efficient simulation of spatially heterogeneous biochemistry in comparison to alternative methods and this is demonstrated via a Michaelis-Menten benchmark test. At the end, I will describe recent work in collaboration with the Faeder and Murphy Labs on immune cell signaling. While not directly related to self-assembly or the methods described previously, this collaboration allowed me to design a kinetic model from scratch and to develop an optimization framework tailored to real experimental data.

Thesis Committee:
Russell Schwartz (Chair, CMU)
James Faeder (University of Pittsburgh)
Frederick Lanni (CMU/Biology Department)
Timothy Lezon (University of Pittsburgh)

Zoom Participation.  See announcement.

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