2026 Research in the Capitol
Presentation Type
Poster Presentation (UNI Access Only)
Abstract
RAD51 proteins bind to single-stranded DNA and are assembled into cooperative nucleoprotein filaments that are essential in DNA repair. In order to capture the stochastic nature of this process, we developed a Dynamic Monte Carlo simulation that models nucleoprotein polymerization on a DNA lattice. To connect the simulation with mass photometry data, we applied Expectation-Maximization (EM) and Nonlinear least squares (NLS) fitting to fit Gaussian mixture models to model polymer size distributions.
Start Date
9-3-2026 11:30 AM
End Date
9-3-2026 1:30 PM
Event Host
University Honors Programs, Iowa Regent Universities
Faculty Advisor
Ali Tabei
Department
Department of Physics
Copyright
©2026 Addison Cunningham, Clare Wright, Sander Tompkins, and Ali Tabei
File Format
application/pdf
Recommended Citation
Cunningham, Addison; Wright, Clare; Tompkins, Sander; and Tabei, Ali, "Stochastic Modeling of Nucleoprotein Oligomerization and Parameter Estimation from Mass Photometry Data" (2026). Research in the Capitol. 14.
https://scholarworks.uni.edu/rcapitol/2026/all/14
Stochastic Modeling of Nucleoprotein Oligomerization and Parameter Estimation from Mass Photometry Data
RAD51 proteins bind to single-stranded DNA and are assembled into cooperative nucleoprotein filaments that are essential in DNA repair. In order to capture the stochastic nature of this process, we developed a Dynamic Monte Carlo simulation that models nucleoprotein polymerization on a DNA lattice. To connect the simulation with mass photometry data, we applied Expectation-Maximization (EM) and Nonlinear least squares (NLS) fitting to fit Gaussian mixture models to model polymer size distributions.
