Bryan S. Briney

The paper shows that early clonal dominance in B-cell precursors after vaccination predicts the breadth of HIV-neutralizing antibodies in rhesus macaques.

The paper analyzes changes in the human antibody repertoire over four years using high-throughput sequencing, finding conservation of broad features but changes in fine details.

This study evaluates MoE architectures for antibody language models, finding token-choice routing improves performance by specializing in CDRH3 residues and enabling efficient pre-training.

This study identifies T-bet expressing B cells as critical for mucosal immunity and protection against norovirus infection through IgG and IgA responses.

This study shows that a germline-targeting HIV immunogen induces cross-neutralizing antibodies in outbred macaques by priming V2-apex bnAb B cell precursors.

This study vaccinates nonhuman primates with SARS-CoV-2 and MERS-CoV spike proteins to elicit cross-reactive antibodies that neutralize both sarbecoviruses and merbecoviruses.

This study determines the structure of HAstV spikes bound to FcRn, identifies conserved epitopes, and suggests repurposing FcRn inhibitors for antiviral therapy.

GhostFold generates synthetic multiple sequence alignments (MSAs) from single sequences to improve protein structure prediction, achieving accuracy comparable to existing methods without relying on homology searches.

This study profiles B cell development using single-cell RNA sequencing, revealing proliferative bursts after recombination and repertoire changes during lymphopoiesis.

This paper introduces a curriculum learning approach for training antibody language models, showing that a 650M-parameter model outperforms existing mixed models in downstream tasks.

This study derives a scaling law for antibody language models, showing that performance improvements require both large model size and sufficient data.

This study shows that targeting the conserved HIV fusion peptide with modified Env immunogens in rhesus macaques can focus immune responses on neutralizing epitopes.

This paper introduces a preferential masking strategy for antibody language models to improve prediction of non-templated residues in CDR3 regions, enhancing classification and specificity.

This paper uses AI to predict and stabilize the conformational states of Lassa virus GPC, identifying vaccine candidates with improved expression and antigenicity.

This study uses AlphaFold3 to model structural dynamics of DNA ligases, revealing conformational changes critical for enzyme function and DNA repair.

The paper demonstrates how open innovation competitions improve computational biology methods for antibody clustering, gene expression imputation, and CMap querying.

The paper develops ab[x], a scalable software toolkit for genetic analysis of antibody repertoire data, including cloud deployment, preprocessing, and downstream analysis tools.