Foundations of Computational and Systems Biology (M-I-T)

• 1. Introduction to Computational and Systems Biology
• 2. Local Alignment (BLAST) and Statistics
• 3. Global Alignment of Protein Sequences (NW, SW, PAM, BLOSUM)
• 5. Library Complexity and Short Read Alignment (Mapping)
• 6. Genome Assembly
• 7. ChIP-seq Analysis; DNA-protein Interactions
• 8. RNA-sequence Analysis Expression, Isoforms
• 9. Modeling and Discovery of Sequence Motifs
• 10. Markov and Hidden Markov Models of Genomic and Protein Features
• 11. RNA Secondary Structure; Biological Functions and Predictions
• 12. Introduction to Protein Structure; Structure Comparison and Classification
• 14. Predicting Protein Interactions
• 15. Gene Regulatory Networks
• 16. Protein Interaction Networks
• 17. Logic Modeling of Cell Signaling Networks
• 18. Analysis of Chromatin Structure
• 19. Discovering Quantitative Trait Loci (QTLs)
• 20. Human Genetics, SNPs, and Genome Wide Associate Studies
• 21. Synthetic Biology From Parts to Modules to Therapeutic Systems
• 22. Causality, Natural Computing, and Engineering Genomes
• Lecture 13. Predicting Protein Structure