- Introduction (1 lecture)
- Course logistics
- Short intro to molecular biology
- Introduction to probabilistic models for computational biology (3 lectures)
- Bayesian network representation
- Maximum likelihood estimation, expectation maximization algorithm
- Systems biology (5 lectures)
- Gene regulation basics, microarray data analysis
- Learning regulatory networks
- Systems genetics, network medicine
- Finding regulatory motifs
- Inferring signaling networks
- Genetics (5 lectures)
- Genetics basics, QTL mapping
- Human genetics basics, genome-wide association studies (GWAS)
- Haplotype reconstruction
- Imputation, tagging SNP selection
- Other issues in GWAS, two-point linkage analysis
- Sequence analysis (3 lectures)
- DNA, RNA sequence analysis
- Computational cancer biology (2 lectures)
Dates for Assignments
- Problem set 1: out 10/3. due 10/17.
- Problem set 2: out 10/17. due 10/31.
- Problem set 3: out 10/31. due 11/14.
- Problem set 4: out 11/14. due 12/3.
Dates for Project Assignments
- Project proposal: due 10/10. - extended to 10/17
- Midterm report: due 11/7. - extended to 11/14
- Final report: due 12/14.
- Final presentations or poster session: on 12/5. - postponed to 12/12
Late Day Policy
All assignments are due at the beginning of class (11:59am) on the assigned due date. We recognize that students may encounter unexpected circumstances and so require more flexibility in the course schedule. Therefore, each student will be granted a total of 3 free late (calendar) days that can be applied to every assignment, but not the final report submission.