Lecture Notes

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SES # TOPICS
L1 Algorithms; Machine Learning; Biology (PDF - 1.9 MB)#
L2 Evolutionary Models; Seq Alignment; Dynamic Programming (PDF)#
L3 Local/Global Alignments; Variations on Dynamic Programming (PDF)#
L4 Linear Time String Searching; Suffix Trees; String Preprocessing (PDF)
L5 Database Search; Hashing; Random Projections (PDF - 2.1 MB)
L6 Biological Signals; HMMs (PDF)
L7 CpG Islands/Simple ORFs; Learning with HMMs (PDF)
L8 Expression Analysis; Clustering (PDF)
L9 Multi-dimensional Clustering; Feature Selection (PDF)
L10 Regulatory Motifs; Gibbs Sampling; Expectation Maximization (PDF)#
L11 Biological Networks; Graph Algorithms (PDF)
L12 Phylogenetic Trees; Greedy Algorithms; Parsimony; EM (PDF)
L13 Multiple Alignment; Profile Alignment; Iterative Alignment (PDF)#
L14 Midterm
L15 RNA Folding; Context-free Grammars; Phylo-CFGs (PDF)
L16 Combine Alignment and Feature Finding; Pair HMM (PDF)
L17 Gene Finding; Generalized HMMs
L18 Comparative Gene Finding; Phylogenetic HMMs (PDF - 4.1 MB)
L19 microRNA Regulation; Target Prediction (PDF)
L20 Regulatory Relationships; Bayesian Networks
L21 Generative Models of Regulation; Bayesian Graphs
L22 Genome Assembly; Euler Graphs
L23 Genome Duplication; Genome Rearrangements (PDF)# (Courtesy of Michael Brudno. Used with permission.)
L24 Whole-genome Comparative Genomics
L25-L26 Final Presentations