Gur Yaari

Our laboratory develops computational, statistical, and machine learning methods for the analysis of high-throughput biological data. Our research is highly interdisciplinary, integrating concepts and approaches from mathematics, statistics, physics, computer science, biology, and medicine. The primary focus of our work is the adaptive immune system, studied from a systems-level and immune repertoire perspective.

We are particularly interested in understanding the generation, evolution, and dynamics of B cell and T cell repertoires in health and disease. Our research spans a wide range of biological and clinical contexts, including infection, vaccination, autoimmunity, aging, and cancer. By combining cutting-edge molecular and genomic technologies with advanced computational approaches, we generate and analyze large-scale datasets of immune receptor sequences and related multi-omic measurements.

Through the development of dedicated analytical frameworks and predictive models, we aim to uncover the principles that govern adaptive immune responses, characterize immune repertoire diversity, and identify biomarkers and mechanisms that can improve our understanding of human health and disease.