Systems and Biomolecular Data Science Training Program (SBDS)
The overarching goal of the Systems and Biomolecular Data Science training program (SBDS) is to prepare the next generation of transdiciplinary biomedical scientists at the interface of quantitative biology, systems biology, machine learning and informatics.
UVA has a rich and decades-long history in Systems and Biomolecular Data Science. The training program brings together 12 degree-granting programs and 34 faculty mentors across the School of Medicine, UVA Engineering, the School of Data Science and the Graduate School of Arts and Sciences. The SBDS training program serves as a hub for cultivating quantitative, computational and analytic predoctoral students at the University of Virginia.
What is Systems and Biomolecular Data Science?
For the training program, Systems and Biomolecular Data Science (SBDS) is used to encompass systems biology, computational biology, and molecular-level biomedical data science. Systems biology research involves some type of mathematical abstraction (i.e., a model) of biology that is refined by iterating with experiments. Computational biology research involves the development of new computer algorithms to tackle general challenges in biomedical research. Biomedical data science leverages existing public datasets in ways that generate new knowledge. SBDS trainees have one or more of these three themes featured in their research plan and co-mentorship structure.