Yaari Gur

Biography

Dr. Yaari Gur is affiliated to the Department of Engineering, Bar Ilan University. Dr. Yaari Gur is currently providing services as Doctor. Dr. Yaari Gur has published numerous publications in various national and international peer-reviewed journals and presented scientific papers across the world. Because of the active association with different societies and academies as well as the contributions, Dr. Yaari Gur is been recognized by the subject experts around the world. Dr. Yaari Gur contributions are appreciated by various reputed awards. Dr. Yaari Gur clinical and scientific research interests include develops computational and statistical tools to process and analyze high-throughput biological data. The research is multidisciplinary and involves elements from mathematics, statistics, physics, computer science, biology and medicine. Our main focus is studying the adaptive immune system from a system/repertoire perspective. In particular, we are interested in understanding lymphocyte (T and B cells) repertoire dynamics in healthy individuals as well as in illness states such as infections, autoimmune diseases, aging and cancer. We apply advanced molecular biology methods to produce large sequencing data sets of human lymphocyte receptors, and analyze them using dedicated computational pipelines, in order to obtain meaningful biological insights into the adaptive immune system.

Research Interest

Develops computational and statistical tools to process and analyze high-throughput biological data. The research is multidisciplinary and involves elements from mathematics, statistics, physics, computer science, biology and medicine. Our main focus is studying the adaptive immune system from a system/repertoire perspective. In particular, we are interested in understanding lymphocyte (T and B cells) repertoire dynamics in healthy individuals as well as in illness states such as infections, autoimmune diseases, aging and cancer. We apply advanced molecular biology methods to produce large sequencing data sets of human lymphocyte receptors, and analyze them using dedicated computational pipelines, in order to obtain meaningful biological insights into the adaptive immune system