Welcome to the Sung Research Group at Mayo Clinic!  

Despite many recent innovations in the practice of medicine, there are still significant barriers in the diagnosis, prognosis, and treatment selection for chronic non-communicable diseases. We need much more practical, robust, and scalable solutions for the following: How can we catch diseases early? How can we rapidly diagnose a disease and identify its stage of progression? Which therapy is most likely going to work? How can we more precisely monitor how the patient is recovering? Finally—and most importantly—how can we maintain optimal health?

Working to these ends, we are a systems medicine and biomedical data science laboratory dedicated to solving the most pressing computational challenges in human disease research. Our research interests have two main fronts: The first is the basic discovery end, wherein we study the metabolism of the human gut microbiome. In particular, by using metagenome mining, metabolic pathway analysis, and metabolomic profiling, we aim to identify microbial biochemical features and processes that determine ecological structure and dynamics. The second is the clinical and translational end, in which we specialize in developing computational biomarkers from omics data to guide clinical decision-making. Using concepts and tools from bioinformatics, systems biology, network science, and machine learning, our work is conducted primarily on multi-omic datasets from clinical samples. In addition, we are working in close collaboration with wet lab scientists to integrate experimentation with high-throughput data analyses.

Our group is based in the Divisions of Computational Biology and Rheumatology at Mayo Clinic, and is part of the Microbiomics Program in Mayo Clinic’s Center for Individualized Medicine.