Each summer, the Computational Genomics Course brings together University of Illinois Urbana-Champaign and Mayo Clinic faculty, staff, and students for a week of virtual learning in genomic analysis and computational methods. Offered through the Mayo Clinic & Illinois Alliance for Technology-Based Healthcare, the course combines lectures from Illinois and Mayo Clinic researchers and clinicians with synchronous and self-paced hands-on lab exercises designed to help participants better understand and apply computational genomics. With no prior experience required, the course creates an accessible starting point for researchers and clinicians at different stages of their careers.
After five days of immersive learning, participants leave with more than an introduction to computational genomics. For many Illinois attendees, the experience reshapes how they approach data and analysis and builds confidence with computational tools.
Emily Depke is a neural engineering undergraduate researcher and a Cancer Scholar with the Cancer Center at Illinois (CCIL). She works with the International Cancer Education Conference (ICEC) and JI (Joseph Irudayaraj) Labs. Depke registered for the 2025 Computational Genomics Course to gain hands-on experience with computational tools and a better understanding of how those tools are applied. She had no prior experience in computational genomics but found the course both challenging and rewarding.
“Prior to the course, I had no experience with computational genomics,” Depke said. “While it is true that my lack of previous knowledge added an extra layer of challenge to the course, I feel as though it allowed me to learn much more than I could've imagined.”
Depke described the course as both rigorous and highly supportive, with an environment that encouraged participants to engage fully with the material.
“I would describe the course as considerably challenging, but I would say that there is plenty of help offered during the week,” Depke said. “Additionally, there really is no penalty for making mistakes, so the challenging aspects of the course become exciting and fun.”
Donggyu Park, an undergraduate research intern in the Beckman Institute’s Chemical Imaging and Structures Laboratory, approached the course from a computer science perspective. While the coding components were familiar, the biology and genomics content pushed him to think beyond computer science and offered a clearer view of how computational biology is applied in real-world research.
“As a pure computer science undergraduate with no background in biology or genomics, the course materials were a little bit difficult to understand and catch up in real time,” Park said. “But I think that proves the level of this course is professional enough. This course was a great opportunity to see how computational biology works in real life.”
For Depke, the experience did not end with the final day of the course. In the months that followed, she continued building on what she learned, applying new skills and approaches in both her coursework and research. Her work has included using microscopy and machine learning to help analyze biological molecules and identify points of interest within complex datasets, reinforcing the practical value of computational tools in research settings.
“The applications of computational tools in genomics are what stayed with me the most,” Depke said. “Since completing the course last June, I have worked with similar data in courses and research labs. The data simulations and large language model applications reviewed in the course set me up well for similar tasks that I have needed to complete for my studies.”
The course influenced how Depke approaches computational genomics and machine learning, prompting her to think more broadly about how these methods can be applied.
“The course encouraged me to think outside of the box in terms of computational genomics and machine learning,” Depke said. “It is easy to grow accustomed to one method of approaching AI and genomics, but taking the Computational Genomics Course helped me see different ways of engaging in these subjects.”
Hosted by the Carl R. Woese Institute for Genomic Biology (IGB), the course is co-led on the Illinois side by Associate Professor of Statistics and Director of Computational Genomics at the IGB, Dave Zhao, with technical support provided by the IGB and the HPCBio Group from the Roy J. Carver Biotechnology Center. This collaboration helps support the instructional and hands-on components of the course each year.
For Zhao, one of the program’s greatest strengths is its ability to give participants a practical starting point in computational genomics and introduce approaches that can be useful across biological disciplines.
“When participants are new to this field, they may find that there are so many tools and perspectives out there that sometimes it helps to have a good place to start,” Zhao said. “The perspectives provided by Illinois and Mayo experts can serve as a guide through this fast-developing field.”
Asked how the course has evolved in recent years, particularly with the growing role of artificial intelligence and machine learning in genomics research, Zhao pointed to ongoing updates that keep the course aligned with current research needs. The 2025 schedule included new modules on Long Reads and AI for Digital Pathology, demonstrating the continued focus on emerging technologies and modern research workflows.
“We update the course every year to stay on top of the latest experimental and technological developments,” Zhao said. “For example, in recent years, we’ve added modules on single-cell and spatial transcriptomics and AI. Our goal each year is to show participants what a modern research workflow looks like in genomics.”
More than 1,000 researchers have completed the course since 2013, reflecting its longstanding role in helping participants build practical skills in computational genomics. Previous participants have described the course as a valuable way to expand their genomic toolkit and apply new methods directly to their own research, from microbiology and veterinary medicine to computational biology.
“I would tell an Illinois researcher or student who is considering taking this course to keep an open mind and to make the most of the resources that the course provides,” Depke said. “There really is a lot to gain from the course, and they have the opportunity to learn a lot if they put their mind to it.”
Registration is now open for the 2026 Computational Genomics Course, a one-week intensive program designed to help researchers and clinicians build practical skills in genomic analysis and apply them in their current and future work. The course will be held virtually June 22–26, with registration open through June 15. No prior experience in computational genomics or coding is required. Full course details and registration information are available on the course website. Contact IHSI Clinical Partnerships Manager LeaAnn Carson with questions.