M. E. Birnbaum

Machine learning model interpretations explain T cell receptor binding

The paper uses machine learning to predict TCR-pMHC binding and identifies sequence features associated with binding affinity.

The T cell receptor sequence influences the likelihood of T cell memory formation

The study identifies TCR sequence features that influence T cell memory formation and positive selection across different T cell lineages.

High-density microbioreactor process designed for automated point-of-care manufacturing of CAR T cells

This paper introduces a high-density microbioreactor for automated CAR T cell manufacturing, achieving clinical dose levels in a small footprint with comparable functional attributes to traditional methods.

Decoupled neoantigen cross-presentation in tumors with high intratumor heterogeneity reduces dendritic cell activation to limit anti-tumor immunity

This study shows that clonal neoantigen expression enhances dendritic cell activation and anti-tumor immunity, while subclonal expression reduces it in tumors with high intratumor heterogeneity.

Yeast display platform for expression of linear peptide epitopes to assess peptide-MHC-II binding in high-throughput

This paper introduces a yeast display platform for high-throughput assessment of peptide-MHC-II binding by decoupling MHC-II expression from peptides.

An unbiased characterization of the HLA-E and CD94/NKG2x peptide repertoire reveals peptide ligands that skew NK cell activation

The paper identifies 500 HLA-E-bound peptides that bind CD94/NKG2A or CD94/NKG2C, revealing ligands that modulate NK cell activation.

Identification of highly cross-reactive mimotopes for a public T cell response in murine melanoma

The paper identifies a dominant tumor-associated antigen in murine melanoma and shows that engineered mimotopes can induce cross-reactive T cell responses.

A high-throughput yeast display approach to profile pathogen proteomes for MHC-II binding

The paper presents a high-throughput yeast display method to assess MHC-II binding of peptides from SARS-CoV-2 and dengue virus, identifying binders missed by computational predictions.

Leukemia-intrinsic determinants of CAR-T response revealed by iterative in vivo genome-wide CRISPR screening.

This study identifies leukemia-intrinsic resistance mechanisms to CAR-T therapy through in vivo CRISPR screening in a murine B-ALL model, revealing IFNγ/JAK/STAT and antigen processing pathways as key mediators.

Antigen identification and high-throughput interaction mapping by reprogramming viral entry

This paper introduces RAPTR, a method to identify antigens and map their interactions with immune receptors using viral pseudotyping and single-cell sequencing.

CARPOOL: A library-based platform to rapidly identify next generation chimeric antigen receptors

The paper develops a library-based platform to identify optimized chimeric antigen receptors (CARs) with improved anti-tumor functions through high-throughput screening of diverse signaling domains.

Extracting and Interpreting the Effects of Higher Order Sequence Features on Peptide MHC Binding

This paper extracts and interprets sequence features affecting peptide MHC binding using yeast display data, showing they accurately predict binding and align with structural knowledge.

Vaccination reshapes the virus-specific T cell repertoire in unexposed adults

This study examines how pre-existing T cell characteristics influence the immune response to a yellow fever vaccine, finding that memory T cells and rare populations shape post-vaccination responses.

Machine learning optimization of peptides for presentation by class II MHCs

The paper develops a machine learning method to optimize peptide binding to class II MHCs by modifying anchor residues, validated through a yeast display assay.

Rapid Assessment of T-Cell Receptor Specificity of the Immune Repertoire

This paper introduces RACER, a pairwise energy model that assesses TCR-peptide affinity using supervised machine learning, demonstrating its utility in simulating thymic selection and estimating recognition rates for tumor antigens.

Antibody Complementarity Determining Region Design Using High-Capacity Machine Learning

This paper introduces a machine learning method to design human IgG antibodies with superior target affinity and specificity, using high-throughput data without requiring target structural information.

Longitudinal immunosequencing in healthy people reveals persistent T cell receptors rich in public receptors

This study tracks T cell receptor beta diversity in healthy individuals over a year, finding persistent receptors linked to antigen exposure history and stable repertoire features.