There has been a great increase in the amount of biomedical data over the past decade. Along with the expanding application of large-scale genomic sequencing, other modalities such as mobile health (mHealth) data and imaging have added to the rise. At the same time, computing power and storage capacity have continued to increase, allowing us to now mine and model biomedical data with unprecedented ability. Together, these trends have given rise to the new field of biomedical data science. The calculations in biomedical data science range from simple statistical associations to complex machine learning models, to simulations of molecular, cellular, and organismic systems.
From basic biological research to clinical investigation, the need for the tools of biomedical data science is ever-expanding. The Center for Biomedical Data Science (CBDS) taps the broad expertise of investigators of the Yale community. CBDS has a number of missions. First, it serves as a focus for the emerging data science community in biomedicine at Yale. Second, it enhances research in the broad area of biomedical data science. Third, CBDS functions as an educational hub with the goal of helping to train the next generation of biomedical research pioneers. Finally, it helps organize infrastructure, both physical and computational, to help facilitate its research and educational missions.
Our goal is to establish a community that fosters collaboration and the free exchange of ideas among diverse investigators working in all areas of biomedical data science at Yale. We welcome you to join us.