Calendar
The calendar below provides information on the course's lecture (L) and recitation (R) sessions.
Abbreviations
SVM = support vector machine
HMM = hidden Markov model
EM = expectation maximization
NJ = neighbor joining
ML = maximum likelihood
| SES # | TOPICS | ASSIGNMENTS |
|---|---|---|
| L1 | Introduction: biology, algorithms, machine learning | Problem set 1 |
| R1 | Recitation: probability, statistics, biology | |
| L2 | Global / local alignment, dynamic programming | |
| L3 | String search, BLAST, database search | |
| R2 | Recitation: affine gaps alignment, hashing with combs | |
| L4 | Clustering basics, gene expression, sequence clustering | Problem set 2 |
| L5 | Classification, feature selection, SVM | |
| R3 | Recitation: microarrays | |
| L6 | HMMs 1: evaluation, parsing | Problem set 3 |
| L7 | HMMs 2: posterior decoding, learning | |
| R4 | Recitation: posterior decoding review, Baum-Welch learning | |
| L8 | Generalized HMMs and gene prediction | |
| L9 | Regulatory motifs, Gibbs sampling, EM | |
| R5 | Recitation: entropy, information, background models | |
| L10 | Gene evolution: phylogenetic algorithms, NJ, ML, parsimony | Problem set 4 |
| L11 |
Molecular evolution, coalescence, selection, Ka/Ks Guest lecturer: Daniel Neafsey, Broad Institute |
|
| R6 | Recitation: gene trees, species trees, reconciliation | |
| L12 |
Population genomics: fundamentals Guest lecturer: Pardis Sabeti, Harvard Systems Biology |
|
| L13 |
Population genomics: association studies Guest lecturer: Pardis Sabeti, Harvard Systems Biology |
|
| R7 | Recitation: population genomics | |
| L14 | Midterm | Project phase I |
| L15 | Genome assembly, Euler graphs | |
| R8 | Recitation: brainstorming for final projects | |
| L16 | Comparative genomics 1: biological signal discovery, evolutionary signatures | |
| L17 | Comparative genomics 2: phylogenetics, gene and genome duplication | |
| L18 | Conditional random fields, gene finding, feature finding | |
| L19 | Regulatory networks, Bayesian networks | Project phase II |
| L20 | Inferring biological networks, graph isomorphism, network motifs | |
| L21 | Metabolic modeling 1: dynamic systems modeling | |
| L22 | Metabolic modeling 2: flux balance analysis and metabolic control analysis | |
| L23 |
Systems biology Guest lecturer: Uri Alon, Weizmann Institute of Science |
Project phase III |
| L24 |
Module networks Guest lecturer: Aviv Regev, Broad Institute |
|
| L25 |
Synthetic biology Guest lecturer: Tom Knight, MIT Computer Science and Artificial Intelligence Laboratory |
|
| L26 | Final presentations |
