Introduction to Biology
1 The Central Dogma: Some Algorithms Introduction
Enumerative Solutions: Partial Digest Problem and Median Strings
2 Partial Digest Problem Problem set 1 out
3 Motifs and Median Strings
Dynamic Programming: Sequence Alignments
4 Global Alignment Problem set 2 out
5 Local Alignment
6 Spliced Alignment
7 More Efficient Alignment
Graph Theory: Sequencing Genes and Proteins
8 Genomics and SBH Graphs Problem set 3 out
9 Peptide Graphs
Pattern Matching: Exact Matches, Gapless Alignments, and BLAST
10 Exact Pattern Matching Problem set 4 out
11 Suffix Trees
12 Suffix Arrays and BWTs
Clustering: Microarrays and Phylogeny
14 Clustering (Guest Lecturer) Problem set 5 out
15 Trees
Neighbor Joining
16 Review of Phylogenetic Analysis

Coalescent Theory in Biology
17 Application: Microarrays (Guest Lecturer)
Probabilistic Models and Machine Learning: Gene Annotation and Evolution
18 Hidden Markov Models I Problem set 6 out
19 Hidden Markov Models II
20 Gibbs Sampling
21 Random Projections
22 MCMC and Bayesian Networks
23 The Future: Protein Structure (Guest Lecturer)
24 The Future: Haplotype Mapping (Guest Lecturer)
25 Presentations of Final Projects
26 Presentations of Final Projects (cont.)