Over 2.5 quintillion terabytes of data are generated every day from online activities, and while most of this data is from social and financial transactions, the rate of data generation for science and health-related activities is growing at an astounding rate.  The online repository of scientific publications, PubMed, has over 20 million entries, and is growing at a rate of 4%, and nearly all major medical centers now have Electronic Health Records (EHRs) that record thousands of health events daily.

The explosive increase in digitized biomedical data, from basic biology to clinical care, is fundamentally changing how research is performed.  Recognizing and rising to this challenge, the Cleveland Institute for Computational Biology (CICB) was founded in November, 2013 as an academic collaboration between Case Western Reserve University, University Hospitals Case Medical Center, and the Cleveland Clinic.  The CICB will use the combined resources and expertise of these institutions to achieve its mission.

The Cleveland Institute for Computational Biology will advance fundamental knowledge of human biology through the application of computational methods to large and diverse datasets.  Further, the CICB will promote the translation of this knowledge into better diagnosis, prognosis, treatment, prevention and delivery of healthcare.  Key elements of our mission include:

The CICB provides administrative and research infrastructure that assembles a wide variety of research data from many researchers into a standardized and harmonized single place.  Researchers can rapidly find the data they need or find other researchers with whom they can collaborate.

Massive amounts of health information are collected daily into electronic health records (EHRs) as people are seen by doctors, in clinics, and in hospitals.  By removing identifying information and with permission, these data can be used for biomedical research, providing extremely large datasets that can greatly increase our ability to learn new things. By using the data from our multiple participating institutions, we can get a clear picture of healthcare across Cleveland.

There are many different types of data that are collected by doctors, by basic researchers, and by those who study the environment.  These datasets are often extremely large and continually growing, and need new ways of being analyzed.  By developing new computational methods for tying these data together, we can make new discoveries and better understand their connections to each other and their influences on human health.

The digital revolution requires a new way of looking at and analyzing data. There is a great need for people with the education and management skills who can do this. Coordinating across various institutions, we support the training of students at the undergraduate, graduate, and post-graduate levels through courses, seminars, workshops, and fellowships.