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Project
Predicting and modeling of vaccine-induced immune response with immunoinformatics and immunosequencing
High throughput sequencing allows characterization of the human immune system, but the resulting data cannot simply be translated into clinical insights. We have therefore developed artificial intelligence models that can translate T-cell receptor and gene expression data into useful insights about an individual's immune status. For example, we have developed the first online platform to predict the epitopes of T cells. We have demonstrated the power of this for predicting and modeling vaccination-induced immune responses.
Date:4 Jul 2022 → 31 Dec 2022
Keywords:VACCINOLOGY, MACHINE LEARNING, SEQUENCE ANALYSIS
Disciplines:Analysis of next-generation sequence data, Vaccinology