Bioinformatics in Diagnostic Genetics I

Catalog description

This course is an introduction to Bioinformatics – rapidly evolving science at the interface of computers and diagnostic genetics and genomics - with emphasis on molecular evolutionary and key algorithmic foundations. Thus, this course provides a conceptual framework underlying much of modern bioinformatics. Moreover, students will gain hands on experience with computer programs useful for context-driven analyses, data mining and discovery and characterization of gene/RNA/protein/genome sequences, evaluation of DNA/RNA/protein molecules as putative diagnostic markers through basic comparative genomic analyses applications based on Dynamic Programming, Hidden Markov Models, Bayesian Probability, Euler and de-Bruijn graphs, Burroughs-Wheeler transform etc. Students are assigned an independent project (PICCDIn) to demonstrate their aptitude and active learning skills (theoretical and Lab-based) through development of a bioinformatics pipeline epidemiological surveillance bacterial and viral genome sequences. This course runs in tandem with DG6110 (Bioinformatics Labs). This course is a part of the Project-based Integrated Core Curriculum Development Initiative (PICCDIn).