Major Topics: PDB • UniProt • Multiple Sequence Alignment (MSA) • BLAST • HHblits • Phylogenetics

Module 2 — Structural Bioinformatics | Week 2 Explore essential structural bioinformatics resources and sequence-analysis concepts used in computational protein research.

Major Topics: DNA • RNA • Proteins • Amino Acids • Protein Folding

Module 1 — Molecular Biology Fundamentals | Week 1 Develop the biological foundation required for protein structure prediction.

Module 3 — Deep Learning Foundations | Week 3 Understand important AI concepts behind modern protein-prediction systems.

Major Topics: Transformers • Attention • Graph Neural Networks (GNNs) • Protein Embeddings

Module 4 — AlphaFold Fundamentals | Week 4 Explore the development of protein structure prediction and the evolution of AlphaFold.

Major Topics: AlphaFold History • CASP • AlphaFold 1–3 • Traditional Protein Structure Prediction Methods

Major Topics: Evoformer • IPA • Recycling • Confidence Metrics

Module 5 — AlphaFold 2 Architecture | Week 5 Study the major architectural concepts underlying AlphaFold 2.

Module 7 — Advanced Protein AI | Week 7 Explore advanced AI approaches and tools used within computational protein science.

Major Topics: AlphaFold-Multimer • Protein Language Models • OpenFold • Drug Discovery

Module 8 — Research & Capstone | Week 8 Apply course concepts to research-oriented problems and explore responsible applications of AI in biomedical science.

Major Topics: Biomedical Applications • Benchmarking • Ethics • Final Project