Covers the algorithmic and machine learning foundations of computational biology  combining theory with practice Principles of algorithm design  influential problems and techniques  and analysis of large-scale biological datasets Topics include (a) genomes: sequence analysis  gene finding  RNA folding  genome alignment and assembly  database search  (b) networks: gene expression analysis  regulatory motifs  biological network analysis  (c) evolution: comparative genomics  phylogenetics  genome duplication  genome rearrangements  evolutionary theory