The Institute, housed at Case Western Reserve University, convenes a wide range of researchers and professionals for intellectual exchange, to support one another’s work, and to serve as consultants on a variety of inquiries.

We lead and/or support regional, national, and international collaborations that seek to improve individual, public, and population health drawing on related disciplines:

• Genetic and population epidemiology
• Genomic variation
• Translational clinical research

Mission

The Cleveland Institute for Computational Biology advances fundamental knowledge of human biology through the application of computational methods to large and diverse datasets. We promote the translation of our work into better diagnosis, prognosis, treatment, prevention, and delivery of health care to individuals and communities.

Values

We consider a 360- degree view of human biology – from the cell to the individual to whole populations. And we champion diversity – from those who frame and conduct the research to all who participate as engaged subjects and controls so that everyone benefits.

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.