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 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

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

  • Precision Health
  • Weil 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
  • Caswell Diabetes Institute
  • Kellogg Eye Center
  • Internal Medicine
  • Michigan Neuroscience Institute
  • Institute for Heart and Brain Health


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 Illustration of a microscope
Health Lab
Researchers uncover distinct molecular subgroups of kidney disease for personalized treatment
Researchers have used advanced computer algorithms to uncover distinct molecular subgroups of kidney diseases, independent of clinical classifications. These findings have significant implications for personalized treatment approaches.
Florescent image of a human ovarian follicle
Health Lab
Spatial atlas of the human ovary with cell-level resolution will bolster reproductive research
New map of the ovary provides a deeper understanding of how oocytes interact with the surrounding cells during the normal maturation process, and how the function of the follicles may break down in aging or fertility related diseases.
AI-generated fantasist illustration with two identical cells in a blueprint style
Department News
A new grant for the Rajapakse lab
The Rajapakse lab receives a new grant.
Department News
Jun Li inducted into 2024 Class of AIMBE College of Fellows
Jun Li was inducted into the 2024 Class of the AIMBE College of Fellows.
Department News
Stephen C.J. Parker, Ph.D., receives 2024 Outstanding Scientific Achievement Award from American Diabetes Association (ADA)
Stephen C.J. Parker, Ph.D., is the recipient of the 2024 Outstanding Scientific Achievement Award from the American Diabetes Association (ADA).
Blue image of a microscopic helix strand
Health Lab
Researchers discover urine based test to detect head and neck cancer
At-home test can detect tumor DNA fragments in urine samples, providing a non-invasive alternative to traditional blood-based biomarker tests