This course focusses on mathematical and computational modelling of various real world processes, with the main focus on biological systems. Using discrete models, algorithmic strategies will be explored including exact algorithms, approximation algorithms, heuristic algorithms, and evolutionary algorithms. The algorithms and models used will involve sets, graphs, strings, trees, machines, and grammars. For each algorithmic technique, we will study applications from biological systems and bioinformatics, including biomolecule string matching, sequence alignment, sequence assembly, gene finding, structure prediction, gene expression data analysis, phylogeny, genome rearrangement, and simulations of molecular evolution. Weekly hours: 3 Lecture hoursPrerequisite(s): CMPT 280.3; and one of BIOL 120.3 or BMSC 200.3 Note: Students with credit for BINF 300.3 or CMPT 813.3 may not take this course for credit. Costs in addition to tuition apply to this course.
This course focusses on mathematical and computational modelling of various real world processes, with the main focus on biological systems. Using discrete models, algorithmic strategies will be explored including exact algorithms, approximation algorithms, heuristic algorithms, and evolutionary algorithms. The algorithms and models used will involve sets, graphs, strings, trees, machines, and grammars. For each algorithmic technique, we will study applications from biological systems and bioinformatics, including biomolecule string matching, sequence alignment, sequence assembly, gene finding, structure prediction, gene expression data analysis, phylogeny, genome rearrangement, and simulations of molecular evolution. Weekly hours: 3 Lecture hoursPrerequisite(s): CMPT 280.3; and one of BIOL 120.3 or BMSC 200.3 Note: Students with credit for BINF 300.3 or CMPT 813.3 may not take this course for credit. Costs in addition to tuition apply to this course.
