Computational Functional Genomics
Lecture Notes
LEC # |
TOPICS |
LECTURERS |
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Part 1: Using DNA Sequence to Explain Mechanism |
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1 |
Course Introduction (PDF) |
David Gifford |
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2 |
Pairwise Alignment (PDF) |
David Gifford |
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3 |
Finding Regulatory Sequences in DNA: Motif Discovery (PDF) |
Tommi Jaakkola |
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4 |
Finding Regulatory Sequences in DNA: Motif Discovery (cont.) (PDF) |
Tommi Jaakkola |
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Part 2: Observing the Mechanism of Transcriptional Regulation |
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5 |
Microarray Technology (PDF) |
David Gifford |
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6 |
Expression Arrays, Normalization, and Error Models (PDF) |
Tommi Jaakkola |
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7 |
Expression Profiles, Clustering, and Latent Processes (PDF) |
Tommi Jaakkola |
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8 |
Computational Functional Genomics (PDF) |
David Gifford |
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9 |
Stem Cells and Transcriptional Regulation |
David Gifford |
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10 |
Part One: An Example of Clustering Expression Data (PDF) |
David Gifford |
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11 |
Project Group Meetings |
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12 |
Project Group Initial Presentations |
Students |
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13 |
Computational Discovery of Regulatory Networks(PDF - 2.3 MB) (Courtesy of Georg Gerber. Used with permission.) |
Georg Gerber (Guest Lecturer) |
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14 |
RNA Silencing (PDF) |
David Bartel (Guest Lecturer) |
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Part 3: Building Predictive Network Models of Transcriptional Regulation |
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15 |
Computational Functional Genomics (cont.) (PDF) |
David Gifford |
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16 |
Human Regulatory Networks (PDF) |
David Gifford |
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17 |
Protein Networks |
David Gifford |
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18 |
Causal Models (PDF) |
Tommi Jaakkola |
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19 |
Causal Bayesian Networks, Active Learning (PDF) |
Tommi Jaakkola |
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20 |
From Biological Data to Biological Insight (PDF) |
Nir Friedman (Guest Lecturer) |
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21 |
Modeling Transcriptional Regulation (PDF) |
Tommi Jaakkola |
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22 |
Dynamics |
David Gifford |
Assignments
ASSIGNMENTS |
SUPPORTING MATERIALS |
Problem Set 1 (PDF) |
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Problem Set 2 (PDF) |
Code (ZIP) (The ZIP file contains: 22 .m files.) Data (ZIP - 1.9 MB) (The ZIP file contains: 2 .fasta files.) Code Diagram (JPG) Bound ORFs (FA) Revised Load Sequences (M) |
Problem Set 3 (PDF) |
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Problem Set 4 (PDF) |
Code and Data (ZIP) (The ZIP contains: 1 .ps file, 1 .pdf file, 2 .mat files, and 11 .m files.) |
Projects
An integral part of the course is a student project component that is based on our case study theme of understanding biological mechanism. Interdisciplinary groups of students are encouraged to work together to develop novel analysis methodologies to examine recent data.
Following are examples of student reports on their projects. (Files are courtesy of the authors, used with permission.)
"Modeling the Human Transcriptome using Factor Analysis," by Garrett Frampton (PDF)
"Spectral Clustering for Microrray Data," by Alvin Liang, Cameron Wheeler, and Grant Wang (PDF)
"Using Phylogenomics to Predict Novel Fungal Pathogenicity Genes," by Ying Li, David DeCaprio, and Hung Nguyen (PDF)
"Whole-genome Analysis of GCN4 Binding in S.cerevisiae," by Alex Mallet, and Lillian Dai (PDF)