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Computational Biology: Genomes, Networks, Evolution >> Content Detail



Lecture Notes



Lecture Notes

This section contains documents that could not be made accessible to screen reader software. A "#" symbol is used to denote such documents.


SES #TOPICS
L1Algorithms; Machine Learning; Biology (PDF - 1.9 MB)#
L2Evolutionary Models; Seq Alignment; Dynamic Programming (PDF)#
L3Local/Global Alignments; Variations on Dynamic Programming (PDF)#
L4Linear Time String Searching; Suffix Trees; String Preprocessing (PDF)
L5Database Search; Hashing; Random Projections (PDF - 2.1 MB)
L6Biological Signals; HMMs (PDF)
L7CpG Islands/Simple ORFs; Learning with HMMs (PDF)
L8Expression Analysis; Clustering (PDF)
L9Multi-dimensional Clustering; Feature Selection (PDF)
L10Regulatory Motifs; Gibbs Sampling; Expectation Maximization (PDF)#
L11Biological Networks; Graph Algorithms (PDF)
L12Phylogenetic Trees; Greedy Algorithms; Parsimony; EM (PDF)
L13Multiple Alignment; Profile Alignment; Iterative Alignment (PDF)#
L14Midterm
L15RNA Folding; Context-free Grammars; Phylo-CFGs (PDF)
L16Combine Alignment and Feature Finding; Pair HMM (PDF)
L17Gene Finding; Generalized HMMs
L18Comparative Gene Finding; Phylogenetic HMMs (PDF - 4.1 MB)
L19microRNA Regulation; Target Prediction (PDF)
L20Regulatory Relationships; Bayesian Networks
L21Generative Models of Regulation; Bayesian Graphs
L22Genome Assembly; Euler Graphs
L23Genome Duplication; Genome Rearrangements (PDF)# (Courtesy of Michael Brudno. Used with permission.)
L24Whole-genome Comparative Genomics
L25-L26Final Presentations

 








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