ETD

• ai
• aptamer
• aptamers
• artificial intelligence
• bayesian optimization
• data analysis
• deep learning
• machine learning
• protein
• proteins

This thesis proposes the use of Geometric Deep Learning and Generative Artificial Intelligence for Aptamer Predictive Triage, in order to explore methods to hasten or entirely overcome the traditional SELEX approach.

Recent advancements in Geometric Deep Learning and generative artificial intelligence allow the study of alternative methods for in-silico de-novo aptamer research.

In particular, this approach looks into the possibility of enhancing current methodologies with spatial information about both proteins, aptamers and their binding sites.