Dmitriy M. Chudakov

The paper demonstrates a repertoire-guided workflow to prioritize antibody candidates targeting β-amyloid and its isoAsp7 proteoform, identifying potential heavy-light chain combinations through computational and experimental methods.

The paper develops a high-throughput TCR discovery assay to identify antigen-specific T cells, finding over 90 SARS-CoV-2-specific TCR clonotypes in one donor and nearly 1,000 in five donors.

The paper investigates NK cell antigenic specificity by analyzing scRNA-Seq, single-cell cloning, and in silico modeling to show glycosylation's role in modulating KIR2DS4 interactions with peptide-MHCI complexes.

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.

The paper introduces SANSARA, a method for splicing-aware scRNA-Seq analysis, revealing splicing heterogeneity in T cell subsets and interactions between transcription factors.

This study analyzes T-cell receptor repertoires to identify how thymic selection shapes TCR diversity and lineage commitment through changes in CDR3 properties and MHC haplotype effects.

The paper analyzes B cell subpopulations in lung and renal cancer, finding that FCRL4 expression and IgA/IgG ratios correlate with tumor progression and poor survival.

This paper introduces TCR-Track, a method to map and track helper T cell subsets in scRNA-Seq data, revealing their clonal relationships and functional programs over time.

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

The paper uses template-based modeling to generate TCR:antigen:MHC structures and identifies amino acid contact features that influence antigen recognition.

The paper shows HLA alleles preferentially present peptides from proteins with specific molecular functions, linking these preferences to HLA allele differences and disease susceptibility.