Achieving BCBI’s scientific vision will require not only world-class researchers, but also computational infrastructure designed for a new model of collaborative biomedical research. Increasingly rich and complex datasets are being generated, yet technical, institutional, and regulatory barriers often make it difficult to share and analyze these data across research groups, limiting discoveries that depend on integrating complementary datasets and expertise. At the same time, labs repeatedly encounter common computational challenges and bottlenecks that can be addressed far more effectively through shared solutions. To overcome these barriers, BCBI will establish BioJupyter, a modular, open platform that makes fluid, reproducible, multi-institutional collaboration over shared biomedical data a natural part of the research environment, while integrating modern AI capabilities and respecting data privacy and security requirements. BioJupyter will integrate deeply with JupyterHealth, a new open-source platform being developed jointly by UC Berkeley and UCSF as a development and operational environment for clinical care, creating a bridge between computational and biomedical research and its eventual translation into clinical practice.
