Catalog

Foundations of Computational and Systems Biology

Biology MIT CC BY-NC-SA 4.0 22 lectures

This course is an introduction to computational biology emphasizing the fundamentals of nucleic acid and protein sequence and structural analysis; it also includes an introduction to the analysis of complex biological systems. Topics covered in the course include principles and methods used for sequence alignment, motif finding, structural modeling, structure prediction and network modeling, as well as currently emerging research areas.

Syllabus

  1. 1 Lecture 1: Introduction to Computational and Systems Biology
  2. 2 Lecture 2: Local Alignment (BLAST) and Statistics
  3. 3 Lecture 3: Global Alignment of Protein Sequences (NW, SW, PAM, BLOSUM)
  4. 4 Lecture 4: Comparative Genomic Analysis of Gene Regulation
  5. 5 Lecture 5: Library Complexity and Short Read Alignment (Mapping)
  6. 6 Lecture 6: Genome Assembly
  7. 7 Leture 7: ChIP-seq Analysis; DNA-protein Interactions
  8. 8 Lecture 8: RNA-sequence Analysis: Expression, Isoforms
  9. 9 Lecture 9: Modeling and Discovery of Sequence Motifs
  10. 10 Lecture 10: Markov and Hidden Markov Models of Genomic and Protein Features
  11. 11 Lecture 11: RNA Secondary Structure – Biological Functions and Prediction
  12. 12 Leture 12: Introduction to Protein Structure; Structure Comparison and Classification
  13. 13 Lecture 13: Predicting Protein Structure
  14. 14 Lecture 14: Predicting Protein Interactions
  15. 15 Lecture 15: Gene Regulatory Networks
  16. 16 Lecture 16: Protein Interaction Networks
  17. 17 Lecture 17: Logic Modeling of Cell Signaling Networks
  18. 18 Lecture 18: Analysis of Chromatin Structure
  19. 19 Lecture 19: Discovering Quantitative Trait Loci (QTLs)
  20. 20 Lecture 20: Human Genetics, SNPs, and Genome Wide Associate Studies
  21. 21 Lecture 21: Synthetic Biology: From Parts to Modules to Therapeutic Systems
  22. 22 Lecture 22: Causality, Natural Computing, and Engineering Genomes

Course materials