7.90J | Spring 2005 | Graduate

Computational Functional Genomics

Lecture Notes

Lec # TOPICS LECTURERS
Part 1: Using DNA Sequence to Explain Mechanism
1 Course Introduction (PDF) David Gifford
2 Pairwise Alignment (PDF) David Gifford
3 Finding Regulatory Sequences in DNA: Motif Discovery (PDF) Tommi Jaakkola
4 Finding Regulatory Sequences in DNA: Motif Discovery (cont.) (PDF) Tommi Jaakkola
Part 2: Observing the Mechanism of Transcriptional Regulation
5 Microarray Technology (PDF) David Gifford
6 Expression Arrays, Normalization, and Error Models (PDF) Tommi Jaakkola
7 Expression Profiles, Clustering, and Latent Processes (PDF) Tommi Jaakkola
8 Computational Functional Genomics (PDF) David Gifford
9 Stem Cells and Transcriptional Regulation David Gifford
10 Part One: An Example of Clustering Expression Data (PDF)

Part Two: Computational Functional Genomics (cont.) (PDF)

David Gifford
11 Project Group Meetings  
12 Project Group Initial Presentations Students
13 Computational Discovery of Regulatory Networks (PDF - 2.3 MB) (Courtesy of Georg Gerber. Used with permission.) Georg Gerber (Guest Lecturer)
14 RNA Silencing (PDF) David Bartel (Guest Lecturer)
Part 3: Building Predictive Network Models of Transcriptional Regulation
15 Computational Functional Genomics (cont.) (PDF) David Gifford
16 Human Regulatory Networks (PDF) David Gifford
17 Protein Networks David Gifford
18 Causal Models (PDF) Tommi Jaakkola
19 Causal Bayesian Networks, Active Learning (PDF) Tommi Jaakkola
20 From Biological Data to Biological Insight (PDF) Nir Friedman (Guest Lecturer)
21 Modeling Transcriptional Regulation (PDF) Tommi Jaakkola
22 Dynamics David Gifford

Course Info

Learning Resource Types
Lecture Notes
Projects with Examples