Korea VirusResearch Institute

Adaptive immunity relies on highly diverse repertoires of T cell and B cell receptors that recognize viral antigens. However, linking immune receptor sequences to antigen specificity remains a fundamental challenge due to the enormous diversity of immune repertoires across individuals and populations.

Our research aims to systematically map immune receptor diversity by integrating single-cell immune repertoire sequencing with genetic and clinical metadata, including HLA variation and infection history. Using large-scale datasets and machine learning approaches, we seek to develop predictive models that link immune receptor sequences with antigen recognition. These efforts extend our previous work on population-scale immune diversity and provide a foundation for understanding immune recognition in viral infection.