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Data-driven Drug Discovery

Module code: CHE704P

Credits: 15.0
Semester: SEM2

Contact: Dr Arianna Fornili

The module covers advanced deep learning techniques applied to drug discovery. Topics include chemical datasets for machine learning benchmarking, deep learning for protein structure prediction, binding affinity prediction and virtual screening, and generative models for de novo drug design. Students will learn both how to use existing applications based on machine learning and how to develop deep learning pipelines in the context of drug discovery through hands-on computational sessions.

Connected course(s): UDF DATA
Assessment: 65.0% Examination, 35.0% Practical
Level: 7

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