Understanding how proteins work is key to uncovering how our bodies function, fight disease, and respond to treatments. However, testing each protein in the lab is slow and expensive. This thesis develops new computer models that use artificial intelligence to predict what proteins do and how they do it—right down to the tiny parts of a molecule that make reactions happen. By combining biology with advanced machine learning, these tools make it faster and easier to study proteins, helping scientists design better medicines, enzymes, and treatments for complex diseases.
History
Principal supervisor
Jiangning Song
Year of Award
2025
Department, School or Centre
Biochemistry and Molecular Biology
Campus location
Australia
Course
Doctor of Philosophy
Degree Type
DOCTORATE
Faculty
Faculty of Medicine, Nursing and Health Sciences
Rights Statement
The author retains copyright of this thesis. It must only be used for personal non-commercial research, education and study. It must not be used for any other purposes and may not be transmitted or shared with others without prior permission. For further terms use the In Copyright link under the License field.