Bioinformatics and Computational Biology

World-Class Resources, World-Changing Programs

Computation is the vanguard of today’s biomedical research. UMR’s Bioinformatics and Computational Biology (BICB) program is the vanguard of biomedical computation. We combine the strengths and skills of eight internationally renowned partners - University of Minnesota Rochester, University of Minnesota Twin Cities, Mayo Clinic, IBM, The Hormel Institute, Cray, Inc., National Marrow Donor Program (NMDP), and the Brain Sciences Center - to create a one-of-a-kind opportunity for research and graduate education at the intersection of quantitative sciences, biology, and medicine.

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Save the Date!  

The 9th Annual BICB Research Symposium will take place Thursday, January 12, 2017 at the Rochester Campus.  More information coming soon!

Past Event

The 4th Annual BICB Industry Symposium took place on August 18, 2016.


The University of Minnesota Discover News recently highlighted a new study, co-authored by BICB Ph.D. student Pajau Vangay. The study, “Antibiotics, Pediatric Dysbiosis, and Disease”, was recently published in the scientific journal Cell Host & Microbe. The journal article may lead to new recommendations for antibiotic usage in children, as well as the development of new clinical tests.  Pajau Vangay and her co-authors synthesized current knowledge which revealed that the gut’s microbiome response to antibiotics may be linked to adult disease phenotypes. To see the full journal article, click here.

Scott Simpkins, BICB Ph.D. student, receives National Science Foundation (NSF) Fellowship Honor. Read more >>

Dr. Claudia Neuhauser, named to Fellows of the American Mathematical Society (AMS) for 2013.  Read more >>

Federal Grant
Computational Strategies for Mapping Genetic Interaction Networks, $711,269 NIH award to Chad Myers, Ph.D., 4/1/10–11/30/12. This award will support work on computational methods for deriving quantitative measurements of genetic interactions from colony-based growth assays.  This work will also involve developing strategies for computationally directed iterative genetic interaction screens.