| Lec # | TOPICS | LECTURER | KEY DATES |
|---|---|---|---|
| Part 1: Using DNA Sequence to Explain Mechanism | |||
| 1 | Course Introduction | David Gifford | |
| 2 | Pairwise Alignment | David Gifford | |
| 3 | Finding Regulatory Sequences in DNA: Motif Discovery | Tommi Jaakkola | |
| 4 | Finding Regulatory Sequences in DNA: Motif Discovery (cont.) | Tommi Jaakkola | Problem set 1 due |
| Part 2: Observing the Mechanism of Transcriptional Regulation | |||
| 5 | Microarray Technology | David Gifford | |
| 6 | Expression Arrays, Normalization, and Error Models | Tommi Jaakkola | |
| 7 | Expression Profiles, Clustering, and Latent Processes | Tommi Jaakkola | Problem set 2 due |
| 8 | Computational Functional Genomics | David Gifford | |
| 9 | Stem Cells and Transcriptional Regulation | David Gifford | |
| 10 | Part One: An Example of Clustering Expression Data Part Two: Computational Functional Genomics (cont.) |
David Gifford | Problem set 3 due |
| 11 | Project Group Meetings | ||
| 12 | Project Group Initial Presentations | Students | |
| 13 | Computational Discovery of Regulatory Networks | Georg Gerber (Guest Lecturer) | |
| 14 | RNA Silencing | David Bartel (Guest Lecturer) | |
| Part 3: Building Predictive Network Models of Transcriptional Regulation | |||
| 15 | Computational Functional Genomics (cont.) | David Gifford | |
| 16 | Human Regulatory Networks | David Gifford | |
| 17 | Protein Networks | David Gifford | |
| 18 | Causal Models | Tommi Jaakkola | |
| 19 | Causal Bayesian Networks, Active Learning | Tommi Jaakkola | |
| 20 | From Biological Data to Biological Insight | Nir Friedman (Guest Lecturer) | |
| 21 | Modeling Transcriptional Regulation | Tommi Jaakkola | |
| 22 | Dynamics | David Gifford | Problem set 4 due |