Christophe O. Benoist

The paper introduces immgenT-GP, a gene-program framework that identifies 200 reproducible gene programs in mouse T cells, capturing lineage identity, activation states, and tissue location.

The paper profiles mouse CD4+ T cells across >700 samples to identify 20 molecular states, revealing diverse effector functions and unexpected similarities between Tfh and chronically stimulated states.

The paper defines a unified framework for Treg heterogeneity using a joint RNA-protein model, identifying eight conserved clusters across tissues and conditions.

immgenT creates a comprehensive T-cell molecular atlas across mouse organs and disease states, identifying 8 lineages and 107 clusters using deep generative models and integrating external datasets.

The paper shows that type I interferon primes alveolar epithelial cells for regeneration by enhancing their response to reparative signals from tissue-resident macrophages after viral infection.

The paper analyzes the αβTCR repertoire across 734 mouse samples to uncover patterns in TCR diversity, non-random joining, and clonal expansion.

The paper introduces REPTRA, a contrastive learning model for TCR-epitope recognition using full TCR sequences and a debiased loss function, showing improved performance and highlighting the importance of CDR1 and CDR2.

The paper shows that TCRs from Tregs are more effective than Tconv TCRs in driving pTreg differentiation, with distinct phenotypes based on antigen type.

The paper identifies TCR-V gene usage patterns in T cells sorted by anti-TCR mAbs using single-cell RNAseq and finds enriched ERV1-family LTR expression in specific TRBV regions.

The paper examines T cell changes in mammary glands during pregnancy and lactation, finding an expansion of T effector cells and similarities to intestinal T cells.

This paper introduces DeepAllele, a deep learning model for allele-specific gene regulation analysis, showing improved detection of cis-regulatory elements in F1 hybrid mice immune cells.

The paper identifies a unique population of regulatory T cells in the murine meninges that maintain brain homeostasis by suppressing interferon-gamma-producing lymphocytes and preventing hippocampal damage.

This paper introduces AI-TAC, a convolutional neural network that infers cell-type-specific chromatin activity from DNA sequences using an ATAC-seq atlas of immune cells.

The paper identifies genetic variants affecting chromatin accessibility in T cells and links them to gene expression and autoimmune disease.

This study compares gene modules in human and mouse immune cells, finding conserved transcriptional organization but divergent regulatory mechanisms.