Our research focuses on developing novel computational and experimental strategies for designing next-generation therapeutics, diagnostics and vaccines by combining high-throughput single-cell antibody and T-cell receptor sequencing with artificial machine learning and high-dimensional statistics. Our ultimate aim is to improve public health by decreasing the burden of infectious and autoimmune diseases and cancer.
What are the current driving questions in immune repertoire research?
Cell Syst, 13 (9), 683-686
Access to ground truth at unconstrained size makes simulated data as indispensable as experimental data for bioinformatics methods development and benchmarking
Bioinformatics (in press)
Reference-based comparison of adaptive immune receptor repertoires
Cell Rep Methods, 2 (8), 100269