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The Group

The Laboratory for Systems and Synthetic Immunology is led by Prof. Sai Reddy. It is part of the Department of Biosystems Science and Engineering (D-BSSE) of ETH Zurich, located in the city of Basel.

Our group’s overall research interests are in the emerging fields of systems and synthetic immunology, which are at the intersection of genomics, molecular biotechnology, and immunology.

Systems immunology aims to gain a more comprehensive and quantitative understanding of immune responses using both experimental and computational methods such as high-throughput DNA sequencing and bioinformatics. Synthetic immunology applies molecular and cellular engineering methods to reprogram immune cells for the purpose of controlling and engineering immunity. Methods consist of directed evolution-protein engineering, targeted genome editing, and viral-based gene transfer.

The Laboratory for Systems and Synthetic immunology’s core mission is to use immunogenomics and immune cell reprogramming for applications in biotechnology, vaccination, and immunotherapy.


News

18.05.2017

New article on antibody repertoire predetermination in Cell Reports

New article on antibody repertoire predetermination and stochasticity in Cell Reports Read more 

07.11.2016

Systems Biology of Adaptive Immunity

We welcome you to attend the conference "Systems Biology of Adaptive Immunity" (www.systims2017.ch) that will be held at the ETH venue "Congressi Stefano Franscini" in Ascona, Switzerland, from 14th to 17th May, 2017. Read more 

17.08.2016

New article on reprogramming hybridoma cells in Nature Communications

A new plug-and-(dis)play hybridoma platform enables rapid generation of stable cell lines. Read more 

27.05.2016

Prof. Sai Reddy receives Grand Challenges Explorations grant

Sai Reddy receives the prestigious Grand Challenges Explorations grant for innovative research in global health and development for applied immunology.  Read more 

12.03.2016

New article in Science Advances

A new correction method for error and bias enables highly accurate antibody repertoire sequencing. Read more 

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20.07.2017
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