Prof. Gur Yaari

Computational systems biology:

Using immune repertoires as diagnostic and prognostic tools for diseases.

1. Development of nano-technologies (e.g. lab on a chip) for identification of immune repertoire patterns for diagnostics and prognostics of diseases.

2. Computational investigation of antibody-antigen interactions for antibody engineering.

3. Development and usage of advanced machine learning approaches in various fields.

Lab on a chip, investigation of nano-scale interactions and machine learning applications fit well the nano technology field

Behind the phenomenal success of the human immune system in fighting countless evolving threats lies its ability to diversify, adapt and form long term memory. Specificity is achieved by the dynamic B cells that undergo affinity maturation in response to antigens. Thus, the antibody repertoire stores information about threats that the body has encountered, and can be harnessed to provide valuable information about diseases. We develop computational pipelines tailored for antibody repertoire analyses, and apply them to samples from different clinical conditions to shed light on new disease mechanisms and improve diagnostics and prognostics.