This is an archived course. A more recent version may be available at ocw.mit.edu.

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