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

1. Introduction to Computational and Systems Biology

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)

2. Local Alignment (BLAST) and Statistics

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

3. Global Alignment of Protein Sequences (NW, SW, PAM, BLOSUM)

4. Comparative Genomic Analysis of Gene Regulation

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

Lecture 13. Predicting Protein Structure