Session Key
[L] = Lecture
[R] = Recitation
[E] = Exam
[P] = Presentation
Lecturer Key
[CB] = Christopher Burge
[DG] = David Gifford
[EF] = Ernest Fraenkel
[TA] = Teaching Assistant
[GL] = Guest Lecturer
SES # | TOPICS | LECTURERS | KEY DATES |
---|---|---|---|
L1 | Course Introduction: History of Computational Biology; Overview of the Course; Course Policies and Mechanics; DNA Sequencing Technologies | CB, DG, EF | |
Genomic Analysis | |||
L2 | Local Alignment (BLAST) and Statistics | CB | |
R1 | Statistics; Significance Testing; Bonferroni Correction | TA | |
L3 | Global Alignment of Protein Sequences (NW, SW, PAM, BLOSUM) | CB | Project: Interests Due |
L4 | Comparative Genomic Analysis of Gene Regulation | CB | |
R2 | Clustering, Model Selection, and BIC Scores | TA | |
Genomic Analysis—Next Gen Sequencing | |||
L5 | Library Complexity and Short Read Alignment (Mapping) | DG | Problem Set 1 Due |
R3 | Burrows–Wheeler Transform (BWT) and Alignments. Guest Lecture: Heng Li (Broad Institute) | GL | |
L6 | Genome Assembly | DG | Project: Teams Due |
L7 | ChIP-seq Analysis; DNA-protein Interactions | DG | |
R4 | Simultaneous ChIP-seq Peak Discovery and Motif Sampling | TA | |
L8 | RNA-sequence Analysis: Expression, Isoforms | DG | |
Modeling Biological Function | |||
L9 | Modeling and Discovery of Sequence Motifs (Gibbs Sampler, Alternatives) | CB | |
R5 | Gene Expression Program Discovery Using Topic Models | TA | |
L10 | Markov and Hidden Markov Models of Genomic and Protein Features | CB | |
L11 | RNA Secondary Structure—Biological Functions and Prediction | CB | Problem Set 2 Due |
R6 | Probabilistic Grammatical Models of RNA Structure | TA | |
E1 | Exam 1 | ||
Proteomics | |||
L12 | Introduction to Protein Structure; Structure Comparison and Classification | EF | |
R7 | Protein Amino Acid Sidechain Packing Using Markov Random Fields | TA | Project: Research Strategy Due |
L13 | Predicting Protein Structure | EF | |
L14 | Predicting Protein Interactions | EF | Problem Set 3 Due |
R8 | Protein / Protein Interaction Prediction Using Threading | TA | |
Regulatory Networks | |||
L15 | Gene Regulatory Networks | EF | |
L16 | Protein Interaction Networks | EF | |
R9 | Regression Trees | TA | |
L17 | Logic Modeling of Cell Signaling Networks. Guest Lecture: Doug Lauffenburger | GL | |
L18 | Analysis of Chromatin Structure | DG | Problem Set 4 Due |
R10 | BayesNets | TA | |
Computational Genetics | |||
L19 | Discovering Quantitative Trait Loci (QTLs) | DG | Project: Written Report Due |
R11 | Narrow Sense Heritability | TA | |
L20 | Human Genetics, SNPs, and Genome Wide Associate Studies | DG | |
L21 | Synthetic Biology: From Parts to Modules to Therapeutic Systems. Guest Lecture: Ron Weiss | GL | Problem Set 5 Due |
R12 | Exam Review | TA | |
E2 | Exam 2 | ||
L22 | Causality, Natural Computing, and Engineering Genomes. Guest Lecture: George Church | GL | |
P1 | Presentations | ||
P2 | Presentations (cont.) |