Mark Izraelson

The paper develops a pipeline to identify and track antigen-specific T cell responses to cancer immunotherapy in mice using TCR repertoire analysis.

The paper develops a classifier for detecting SARS-CoV-2 exposure using T-cell repertoire profiling and machine learning, achieving high accuracy across different protocols.

This paper introduces Validator Barcodes (VBCs) as a simpler alternative to UMIs for estimating template molecules in TCR and BCR sequencing, showing comparable results to UMI-based methods.

The paper introduces an algorithm for ultra-sensitive allele inference from immune repertoire sequencing data, demonstrating its accuracy and application in diverse populations.