Medical School
Twin Cities
This group's research centers on bioinformatics data analysis and the development of algorithms and tools for genomics and epigenomics studies, specializing in high-dimensional, large-scale biomedical data analysis. The group has created several bioinformatics tools, including AdCluster for network community structure, GESS for exon skipping detection, ePEST for ChIP-exo analysis, CircularLogo, and Spatial-Live for single-cell spatial-omics. The goal of the research is uncovering the molecular mechanisms underlying biomedical big data through innovative data mining and computational strategies, including by collaboration with wet-lab scientists. Another interest is complex network studies, particularly exploring community structures within biological networks.