DCMB Research
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Translating Theories into Practice

We leverage innovative technologies to investigate how hidden information in genes and biological molecules can further personalize the diagnosis, treatment and prevention of diseases.

Creating Novel AI & Machine Learning Methods to Accelerate Discoveries & Biomedical Research

The research focus of the Gilbert S. Omenn Department of Computational Medicine and Bioinformatics (DCMB) is to create novel and impactful informatics and computationally based AI and Machine Learning methods, tools, algorithms, and information resources to enable and extend basic and clinical research discoveries and methods. 

Working with our students and post-docs, we provide the ideal environment to learn by creating our research and publishing our impactful findings in leading journals. Our research is supported by the National Institutes for Health (NIH), the National Science Foundation (NSF), the Defense Advanced Research Projects Agency (DARPA), and many non-for-profit Foundations and research organizations.

Our faculty engage in a vast spectrum of bioinformatics and computational biology research, analyzing unanswered questions spanning cancers and neuropsychiatric disorders to metagenomics and translational informatics. There is still much to explore at the intersection of biology, computational science, mathematics and medicine. Our faculty are nationally recognized leaders in this highly interdisciplinary field.

More about DCMB Faculty

DCMB Publications

View a collection of publications from the Department of Computational Medicine & Bioinformatics.

View publications on PubMed
WE PUT THE “LAB” IN COLLABORATIVE

By their very nature, computational medicine and bioinformatics are very collaborative. DCMB and CCMB members are engaged with many U-M partners.

  • Caswell Diabetes Institute
  • Center for Metabolic Diseases
  • College of Pharmacy
  • Eisenberg Family Depression Center
  • Frankel Institute for Heart and Brain Health
  • Health Data
  • Internal Medicine
  • Kellogg Eye Center
  • Michigan Neuroscience Institute
  • Precision Health
  • Radiation Oncology
  • Rogel Cancer Center
  • School of Public Health 
  • Weil Institute for Critical Care
Venn diagram illustrating the interdisciplinary nature of dcmb/ccmb machine learning within various biomedical and research sectors at an academic institution.

Graphic that shows DCMB at the core, surrounded by a ring with the various fields of computational medicine and bioinformatics applications. On the outside are "petals" with the name of collaborating units at U-M: Precision Health, Weill Institute for Critical Care, Eisenberg Family Depression Center, Health Data, School of Public Health, Radiation Oncology, Rogel Cancer Center, College of Pharmacy, Center for Metabolic Diseases, Castell Diabetes Institute, Kellogg Eye Center, Internal Medicine, Michigan Neuroscience Institute, and the Institute for Heart and Brain Health. This graphics looks like a flower with a maize and blue core, and colorful petals.

Researcher Database

Explore DCMB's research profile and collaboration network on the Michigan Experts website, a searchable database of research expertise across disciplines from the University of Michigan’s schools, colleges and institutes.

Research Grants

In 2022, DCMB received nearly $75.5 million in funding for 52 grants from organizations including National Science Foundation (NSF), Department of Defense (DoD) and the National Institutes of Health (NIH), for which DCMB ranked #4 in NIH Grants for biomedical science departments.

BAB in the Lab

BioAssemblyBot®, an ultra precise robot affectionately referred to as "she," makes repetition her core mission. Her infatigable ability to precisely repeat the same test using different samples in mere hours gives time back to our scientists to design the best possible experiments.

Get to Know BAB
Featured News & Stories See all news Yufeng Zhang, PhD
Department News
Yufeng Zhang, PhD, defended her bioinformatics dissertation thesis on machine learning models
Zhang's research focuses on developing data-driven identification and prediction systems for real-world medical applications. I am particularly interested in enhancing the generalization and interpretability of machine learning and deep learning models in medicine, as well as exploring innovative methods to improve model accuracy. To address challenges such as the lack of annotated data, limited generalization capabilities, and the need for interpretable models, I have applied several strategies, including privileged information learning, self-supervised learning, and approximate reasoning.
Girls Who Code executive board members
Department News
U-M Girls Who Code receive the Carol Hollenshead Inspire Award for Excellence in Promoting Equity and Social Change
The Carol Hollenshead Inspire Award for Excellence in Promoting Equity and Social Change recognizes faculty, staff and students — either an individual or a group — who have proven that social change is possible through persistent hard work and who demonstrate that one person can make a lasting difference in their communities. Girls Who Code was founded at U-M in 2017 by doctoral students in the Medical School’s Gilbert S. Omenn Department of Computational Medicine and Bioinformatics.
Yiqun Wang at a local farm
Points of Blue
Yiqun Wang, PhD candidate: Giving back to the biomedical field through research
Hy Do is a PhD Candidate in the Bioinformatics Program.
Dr. Stidham in AGA News
Department News
How AI can help physicians: Dr. Stidham's interview in the American Gastroenterological Association News
Dr. Stidham's interview in AGA "GI Docs will need to forge a 'Human-Computer Cooperative'"
Mary Freer receives Presidential Citation from Lynnetta Smith, on behalf of President Ono
Department News
Mary Freer receives a Presidential Citation for her extraordinary service to the University
Mary Freer received a Presidential Citation from President Ono on December 12, 2024
DCMB BGSA activity
Department News
DCMB Trainees - 2024 Highlights
DCMB student highlights for 2024 - Awards and graduation, events.