Read the CCD feature in the Pitt SOM Annual Report.


“Individual biomedical researchers now have the technology to generate an enormous quantity and diversity of data. Adequately analyzing these data to discover new biomedical knowledge remains a major challenge, however,” said Gregory Cooper, MD, PhD, professor and vice chair of the Department of Biomedical Informatics, School of Medicine, and principal investigator on the project. “Our goal is to make it much easier for researchers to analyze big data to discover causal relationships in biomedicine.”

“The good news is that we have so much data. But the bad news is that we have so much data,” said Jeremy M. Berg, PhD, codirector of the center, Pitt’s associate senior vice chancellor for science strategy and planning in the health sciences, and Pittsburgh Foundation Professor of Personalized Medicine. “Our challenge is to find strategies that enable us to sort through all this collected information efficiently and effectively to find meaningful relationships that lead us to new insights in health and disease.”

“The center also will be a training ground for the next generation of data scientists who will advance and accelerate the development and broader use of big data science models and methods,” said center codirector Ivet Bahar, PhD, who is Distinguished Professor, John K. Vries Professor, and chair of the Department of Computational and Systems Biology, School of Medicine. “We will create new educational materials as well as workshops and online tutorials to facilitate the use of causal modeling and discovery algorithms by the broader scientific community and to enable efficient translation of knowledge between basic biological and applied biomedical sciences.”


University of Pittsburgh School of Medicine. (2014) University of Pittsburgh School of Medicine Annual  Report 2014. Retrieved from