Subject Area

Biological Sciences, General, Biophysics, Computer Science, Mathematics, Applied, Molecular Biology

Abstract

We investigate machine learning and electrostatic methods to predict biophysical properties of proteins, such as solvation energy and protein ligand binding affinity, for the purpose of drug discovery/development. We focus on the Poisson-Boltzmann model and various high performance computing considerations such as parallelization schemes.

Degree Date

Spring 2024

Document Type

Dissertation

Degree Name

Ph.D.

Department

Mathematics

Advisor

Weihua Geng

Second Advisor

Wei Cai

Third Advisor

Andrea Barreiro

Fourth Advisor

John Nemunaitis

Number of Pages

125

Format

.pdf

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

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