Immunogenetics & Computational Immunology

Our research aims to decode complex immune responses and translate them into clinically actionable diagnostics. By integrating molecular profiling with computational modeling, we develop data-driven approaches that enable early detection, refined risk stratification, and precise clinical decision-making across immune-mediated conditions. We are particularly interested in the dynamics of immune responses across time and contexts, including transplantation, neuroinflammation, and pregnancy. Our work bridges fundamental and translational questions at the interface of immunogenetics, diagnostics, and computational biology.

Digital Tools & Platforms

Please find all Digital Tools in our online repository

  • Computational analysis of HLA antibody assay-intrinsic reactivity
    Online Framework to support transplant diagnostic laboratories in distinguishing HLA assay-intrinsic reactivity from clinically relevant alloimmunization.

    Tool: HLA_AB_intrinsic_specificity_online_tool

  • Immune Signatures Discovery
    An online machine learning framework leveraging molecular immunological signatures to support patient stratification across diseases and clinical decision-making.

    Publication:  
    (Nature 2024) (Brain 2025)
  • Immune risk modeling in transplantation and pregnancy
    Online Framework to explore how genetic compatibility and immune receptor–ligand interactions shape clinical outcomes.