Martin Hemberg

The Hemberg group specializes in computational genomics, developing innovative algorithms and analytical tools for high-throughput biological datasets while collaborating with experimental teams to drive discovery. Our research operates on two complementary tracks: advancing novel computational methods and partnering with experimental groups to analyze and interpret complex genomics data. These approaches are highly synergistic as challenges emerging from collaborative projects often inspire new methodological innovations, while our tool development frequently opens doors to partnerships applying these methods to unpublished datasets. In all collaborations, we prioritize close partnership with experimentalists to ensure deep data understanding and interpretations grounded in rigorous statistical and computational methodology. Much of our work has centered on single-cell RNA sequencing (scRNAseq), where we have developed methods for unsupervised clustering based on transcriptional and genotypic profiles, cross-dataset mapping, and efficient searching. Beyond transcriptomics, our work covers areas such as transposon detection, microexon identification, liquid biopsies, and cancer mutational characterization. More recent work has focused on multi-omic and spatial transcriptomics technologies. Our overarching goal is to build computational methods that tackle central immunological and genomic questions where existing tools fall short, particularly through integration of large, multi-source datasets.