Computational Biology is a huge field of study, that touches upon many distinct algorithmic and biological areas of study. What we are able to cover in this course will depend, in part, on the pace at which we move, which I will attempt to adjust as appropriate. However, here is a tentative list of topics I hope to cover this semester (not necessarily in order).

• Optimal sequence alignment (global, local, and glocal alignment &mdash with constant & affine gap penalties
• Algorithms and data structures for efficient text indexing and exact search
• Heuristics for read alignment and mapping &mdash mapping DNA-seq and RNA-seq reads
• Genome assembly &mdash k-mers, De Brujin graph construction and representation, long-read technology and read-overlap graph assembly
• Motif finding via Gibbs sampling
• Gene finding &mdash statistical models for ab initio and evidence-guided prediction of genes
• RNA-seq and transcriptomics &mdash transcript assembly, abundance estimation and differential expression testing
• Phylogenetics &mdash The small and large phylogeny problem; parsimony, maximum likelihood and Bayesian methods