Dr. Gur Yaari

Computational Systems Immunology Laboratory

The Alexander Kofkin Faculty of Engineering

 Dr. Gur Yaari joined the BIU Department of Bio-Engineering as a Senior Lecturer in 2013, after a post-doctoral fellowship at Yale University. His Research at BIU focuses on adaptive immunity, from a systems perspective.

Behind the phenomenal success of the immune system in fighting countless threats lies its ability to diversify, adapt and form long term memory. Specificity of the adaptive immune system is achieved by the dynamics of lymphocytes repertoires: T and B cells that following exposure to a threat undergo clonal expansion and selection. B cells in particular go through cycles of somatic hypermutation and affinity driven selection, generating a repertoire of highly specific dedicated antibodies. Thus, the antibody repertoire stores information about specific threats that each individual has encountered, making it a potent candidate to revolutionize the field of personalized medicine.

Dr. Yaari and his team combine experimental and computational expertise to mine biological knowledge from these diverse immune repertoires. They use high throughout sequencing of the variable region of the antibodies, along with dedicated computational algorithms for this task.

Annual Activity Report, March 2017

To date we applied antibody repertoire analysis to a wide range of diseases ranging from cancer to autoimmune diseases. Examples include colon and liver cancer, influenza, multiple sclerosis, celiac, and Hepatitis C virus (HCV) infection. In one study for example, we compared B cell responses between HCV spontaneous clearers and chronic patients, and were able to design broadly neutralizing antibodies based on the sequenced repertoires, as well as to identify an immune signature that differentiates between these responses. This signature can be used to fit a treatment to each patient based on their repertoires. In another ongoing study, we characterize the naïve antibody repertoire of celiac patients, to discover signatures that might enable prediction of the risk for this autoimmune disease in healthy individuals, including disease severity and personalized treatments.


2017 All rights to Dangoor Centre for Personalized Medicine, Bar-ilan University.