| Title: | Bioinformatics methods for precision cardiovascular medicine |
| Lead Institution: | University of Pennsylvania |
| Principal investigator: | Dr Jason Moore |
Application 50978
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
About
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.2 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 3343 | GenNet framework: interpretable deep learning for predicting phenotypes from genetic data | Arno van Hilten (+7) | 2021 | Communications Biology |
| 4886 | Genetic Analysis of Coronary Artery Disease Using Tree-Based Automated Machine Learning Informed By Biology-Based Feature Selection | Elisabetta Manduchi (+3) | 2022 | IEEE Transactions on Computational Biology and Bioinformatics |
Enabling scientific discoveries that improve human health