About CCMB

The U-M Center for Computational Medicine and Bioinformatics (CCMB) is a campus-wide interdisciplinary academic center with over 100 affiliated faculty members. The faculty membership of CCMB has a strong representation from diverse fields such as mathematics, computer science, and statistics, and is complemented by faculty with biological and biomedical expertise who are applying cutting-edge biomedical informatics to their work. CCMB is the University of Michigan institutional leader in the entire spectrum of biomedical informatics disciplines, including bioinformatics, clinical informatics, and health informatics.


Director, CCMB
Gilbert S. Omenn, M.D., Ph.D. (Professor of Internal Medicine, Molecular Medicine & Genetics; Human Genetics; Public Health; Research Professor, DCM&B)

Chief CCMB Administrator
Linda Peasley

CCMB Executive Committee

See CCMB affiliated faculty list.

The CCMB has three major components:

Interdisciplinary Research Program

The Interdisciplinary Research Program provides a coherent collaborative context for the success of existing interdisciplinary research programs and also assists new projects through a pilot grant program. Core interests are data integration and modeling from genomic, transcriptomic, proteomic, and metabolomic studies.

CCMB Seminar Series

The CCMB Seminar Series is held at Palmer Commons or the North Campus Research Complex (NCRC) each Wednesday, at 3:30pm EST, on bioinformatics related topics. Each seminar is presented by an invited guest speaker. These seminars are recorded and made available for future viewing via Flash video streaming on the video archive page.

CCMB Pilot Grants

The goals of the CCMB Pilot Grant Program are to bring together research faculty in different fields (computational/mathematical/statistical/informatics and biological/translational) in joint projects which will foster successful future proposals to NIH or other funding agencies. At least one investigator must be on the roster of CCMB Affiliate Faculty. Proposals should combine the use of computational and informatics capabilities with an important biological or biomedical problem. Innovation on both computational and experimental sides is strongly encouraged.