Principal Investigator: Jason Moore
University of PennsylvaniaTags: 50978, bioinformatics, cardiovascular disease, genetics/genotyping, Machine Learning, Precision Medicine
A central goal of precision medicine is to tailor disease risk assessment, diagnosis, and treatment to specific biochemical, cellular, clinical, demographic, environmental, and genomic characteristics of individual patients or sub-groups from the population for improving health and healthcare. However, there are significant challenges related to developing precision medicine strategies from population-based results, since statistical summaries derived from a human population do not explicitly provide information about the health of an individual. The overarching goal of this 3-year project is the development of bioinformatics methods and software for connecting population-based models of heart failure susceptibility with individual-level measures to advance cardiovascular precision medicine. This will result in a Virtual Genomic Medicine workbench (VGMed) to enable experimentation and hypothesis generation relative to cardiovascular medicine, accelerating the translation of genomic findings relative to heart failure into the clinic.