Medical Bioinformatics: Disease Associations, Protein Folding and Immunogenomics
|Offered this year?||No|
This course is devoted to computational problems and methods in the emerging field of Medical Bioinformatics where genomics, computational biology and bioinformatics impact medical research. We will present challenging problems and solutions in three areas: Disease Associations, Protein Folding and Immunogenomics.
Genome-wide disease association studies (GWAS) present major computational challenges. The goal is to identify inherited genetic variation and its critical role in human disease. Huge datasets containing billions of SNPs, such as the Multiple Sclerosis Consortium GWAS data, will be a subject of our investigations. We will also discuss GWAS analyses for type 2 diabetes (common variants) and mental diseases (rare variants).
The computational protein folding problem, the classical grand challenge of biotechnology, can be stated as follows: can we computationally predict the 3-D native structure of a protein from its 1-D amino acid sequence? Lattice models of protein folding, although unrealistic, contain longstanding unsolved combinatorial and algorithmic problems of exceeding difficulty. Alzheimer's disease has been linked to protein (mis)folding.
Do pathogens evolve their proteomes to avoid the surveillance of the human immune system? Killer T-cells, the 'special forces' of the human immune system, travel throughout the body and eliminate cells that 'display' on their surfaces short pieces of pathogen proteins, called epitopes that are difficult to computationally predict. We will search for epitopes in the immunopeptidomes of H. sapiens, M. musculus, D. melanogaster, HIV, vaccinia, herpesviruses and M. tuberculosis.
This course is open to graduate students and advanced undergraduates with Computational or Life Science backgrounds. Prior background in Biology is not required.