Dr. Thomson's group develops computational methods for constructing predictive models of cell and tissue dynamics from single-cell data sets. A major application of their methods is the modeling of immunologically cold vs active tumors and applying models to design interventions to convert cold tumors to "hot" tumors with significant immune cell infiltration and activation.
Chen, Xiaoqiao, Sisi Chen, and Matt Thomson. "Minimal gene set discovery in single-cell mRNA-seq datasets with ActiveSVM." Nature Computational Science 2.6 (2022): 387-398.
Wang, Zitong Jerry, and Matt Thomson. "Localization of signaling receptors maximizes cellular information acquisition in spatially structured natural environments." Cell Systems (2022).
Brown, D., Altermatt, M., Dobreva, T., Chen, S., Wang, A., Thomson, M., & Gradinaru, V. (2021). Deep parallel characterization of AAV tropism and AAV-mediated transcriptional changes via single-cell RNA sequencing. Frontiers in immunology, 12.
Chen, S., Rivaud, P., Park, J.H., Tsou, T., Charles, E., Haliburton, J.R., Pichiorri, F. and Thomson, M., 2020. Dissecting heterogeneous cell populations across drug and disease conditions with PopAlign. PNAS, 117(46), pp.28784-28794.
Dobreva, T., Brown, D., Park, J. H., & Thomson, M. (2020). Single cell profiling of capillary blood enables out of clinic human immunity studies. Scientific reports, 10(1), 1-9.