BMED 634 Algorithms in Bioinformatics
This course focusses on algorithms to explore the many types of data produced in the Life Sciences, while combining theory and practice. Given the interdisciplinary nature of Bioinformatics, the course highlights the major mechanisms in genetics to an extend that enables formal, algorithmic approaches to process the heterogeneous data from genomics- and proteomics-based technologies: DNA sequence assembly and alignment, functional gene annotation, biological relational databases, metabolic network analysis, comparative genomics, phylogenetics, gene expression analysis and structural bioinformatics. They are coupled with fundamental algorithmic techniques including graph algorithms, dynamic programming, Statistics/Machine Learning, hierarchical clustering, classification and Bayesian methods. We will combine programming (mainly BioPython) and state-of-the- art analysis tools and apply it to Bioenergy, Metagenomics and Biomedicine.
Offered
Fall