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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Encoding and Decoding Specificity in Adaptive Immunity by Deep Learning
Sai Reddy, Ph.D.
Associate Professor
Department of Biosystems Science and Engineering
ETH Zurich
The ability to predict and correspondingly manipulate adaptive immune responses is highly valuable for biotechnology and medicine. To achieve this requires a greater molecular understanding of antigen selection and specificity by adaptive immune cells. In this I will explain how we are using deep learning to identify patterns of antigen-specificity in antibody responses following immunization. Deep neural networks are used to elucidate the antibody sequence space by generating thousands of novel and functional variants in-silico, highlighting how deep learning can be used to encode and decode specificity in adaptive immunity.
