I. Z. Mamedov

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.

The paper identifies non-canonical D1-D2 recombination in T-cell receptor beta chain generation, revealing two types of rearrangements and their role in memory T-cell function.

This study tracks T cell memory formation after mild COVID-19 infection using longitudinal TCR sequencing, showing clonal expansion and memory phenotype acquisition in infected individuals.

The paper tracks T-cell clone dynamics and TCR repertoire changes after primary and secondary yellow fever vaccination using single-cell RNAseq and TCRseq.

This study compares T cell receptor diversity across species, finding that long-lived rodents maintain stable TCR diversity with age, unlike humans and mice.

The paper develops a statistical framework to detect TCR clone changes in vaccinated twins and finds convergent yet personalized TCR responses.

The paper develops a statistical framework to associate antigen receptor sequences with diseases using a small patient cohort, successfully identifying validated receptors for Cytomegalovirus and type 1 diabetes.