CITE-seq

Ancestra: A lineage-explicit simulator for benchmarking B-cell receptor repertoire and lineage inference methods

Ancestra simulates B-cell receptor repertoires with known lineage histories to benchmark clonal grouping and lineage reconstruction methods.

Targeting PD-1+ T-cells with Chimeric Antigen Receptors to reduce the HIV Reservoir

This study designs PD-1-targeting CAR-T-cells to reduce the HIV reservoir by depleting specific T-cell subpopulations in HIV-infected humanized mice.

Distinct contribution of autoreactive B cell Bruton's tyrosine kinase signaling to neuroinflammation

This study shows that deleting BTK in B cells reduces EAE severity by impairing autoreactive B cell functions, supporting BTK as a therapeutic target in MS.

Unsupervised Machine Learning for Adaptive Immune Receptors with immuneML

This paper introduces immuneML, a framework for unsupervised machine learning in adaptive immune receptor repertoires, demonstrating its use in generative modeling, clustering, and dataset analysis.

Deciphering antigen-driven T cell responses through vectorized TCRdist sequence neighborhood quantification

The paper introduces a computational framework to efficiently identify significantly neighbor enriched TCR sequences, demonstrating its utility in analyzing memory T cells and T cell responses to vaccination and viral infections.

Clonal overlap and convergent clustering of T-cell receptor signatures in Crohn's disease in monozygotic twins

This study analyzes T-cell receptor repertoires in monozygotic twins with and without Crohn's disease, finding increased TCR overlap in concordant pairs and identifying eight novel TCR clusters potentially linked to the disease.

Genotype-immunophenotype relationships in NPM1-mutant AML clonal evolution uncovered by single cell multiomic analysis

This study uses single-cell multiomic analysis to reveal genotype-immunophenotype relationships and clonal evolution in NPM1-mutant AML across disease stages.

Human neonatal CITE-seq atlas identifies an immune transition at 32 weeks' gestation from CD15+ myeloid-dominated to interferon-primed immunity

The paper presents a CITE-seq atlas of human neonatal immune development, identifying a 32-week gestational transition to interferon-primed immunity.

Cytotoxicity-based High-throughput Screening System for CAR T Cell

This study develops a high-throughput screening system for CAR T cells based on cytotoxicity, enabling efficient evaluation of CAR designs and identification of superior variants.

Magnetic field-induced ER stress reprograms the tumor microenvironment to improve triple-negative breast cancer survival

Asha therapy induces ER stress in tumor cells, reprograms the tumor microenvironment, and improves survival in triple-negative breast cancer models.

OmicClaw: executable and reproducible natural-language multi-omics analysis over the unified OmicVerse ecosystem.

OmicClaw provides a natural-language framework for reproducible multi-omics analysis using the OmicVerse ecosystem, improving performance over baseline models in complex workflows.

PACMON: Pathway-guided Multi-Omics data integration for interpreting large-scale perturbation screens

PACMON integrates multi-omics data from perturbation screens to infer pathway-level responses to experimental perturbations, achieving high accuracy and scalability.

TCRseek: Scalable Approximate Nearest Neighbor Search for T-Cell Receptor Repertoires via Windowed k-mer Embeddings

TCRseek efficiently searches TCR repertoires using approximate nearest neighbor search with windowed k-mer embeddings, achieving high accuracy and speed.

Single-cell spatial multi-omics molecular pathology enabled by SuperFocus

SuperFocus integrates histopathology with single-cell spatial multi-omics data from spot-based measurements, improving accuracy by 28-73% over existing methods.

Designing mRNA coding sequence via multimodal reverse translation language modeling with Pro2RNA

Pro2RNA generates species-adapted mRNA coding sequences from protein sequences using a multimodal language model, outperforming existing methods in benchmark tests.

Unpaired TCRα + TCRβ sequencing is sufficient for training machine learning TCR-epitope recognition predictors

This study shows that unpaired TCRα + TCRβ sequencing can train accurate TCR-epitope recognition predictors at lower cost than paired sequencing.

Tracking antigen-specific T cell response to cancer immunotherapy

The paper develops a pipeline to identify and track antigen-specific T cell responses to cancer immunotherapy in mice using TCR repertoire analysis.

Maternal obesity induces developmental programming of Intestinal stem cells through an IL-17A/PPAR immune-epithelial axis

This study shows maternal obesity programs intestinal stem cells through an IL-17A/PPAR axis, increasing cancer risk in offspring.

Explainable Graph Learning for Multimodal Single-Cell Data Integration

SCPRO-VI integrates multi-omic single-cell data using a variational graph auto-encoder and biologically guided metrics, improving subcluster identification.

Longitudinal TCR repertoires in ulcerative colitis patients show features distinguishing disease states

This study analyzes TCR repertoires from ulcerative colitis patients over time, identifying Vβ gene usage and K-mer enrichment differences between flare and remission states.

Tissue-specific clonal selection and differentiation of CD4+ T cells during infection

This study uses TRACK mice to show tissue-specific clonal selection and differentiation of CD4+ T cells during influenza infection, revealing organ-specific transcriptional programs and memory formation patterns.

HIV-SEQ REVEALS GLOBAL HOST GENE EXPRESSION DIFFERENCES BETWEEN HIV-TRANSCRIBING CELLS FROM VIREMIC AND SUPPRESSED PEOPLE WITH HIV

The paper develops HIV-seq to capture HIV transcripts for scRNA-seq, revealing distinct transcriptional features of HIV-transcribing cells in viremic and ART-suppressed HIV patients.

Antibody responses against bacterial glycans affinity mature and diversify in germinal centers.

The paper shows that glycan-specific B cells undergo class-switching and diversification in germinal centers with age and infection, influencing vaccine design.

Single Cell Transcriptomics and Surface Protein Expression Reveal Distinct Cellular and Molecular Phenotypes in Human RPESC-RPE and PSC-RPE

The paper compares single-cell transcriptomic and surface protein profiles of RPESC-RPE and PSC-RPE, finding differences in gene expression and surface markers that suggest functional and immunomodulatory differences.

Adult mice with neonatal-like T cell subsets exhibit increased susceptibility to Bordetella pertussis and influenza infection

This study shows that adult mice with neonatal-like T cell subsets are more susceptible to Bordetella pertussis but not influenza, highlighting the role of thymic development in immune responses.

Next-generation all-in-one CRISPR/Cas9 multiply-edited CD30CAR-T cells:Potency despite risk of translocations

This study develops next-generation CD30CAR-T cells using CRISPR/Cas9 for multiplex editing, showing high potency but risks of translocations with combined knockouts.

Integration of single-cell multi-omic data with graph-based topic modelling

This paper introduces a graph-based topic modelling method for single-cell multi-omic data, showing improved performance in clustering and biological interpretation.

Partially Shared Multi-Modal Embedding Learns Holistic Representation of Cell State

APOLLO learns shared and modality-specific information from multi-modal single-cell data to improve understanding of cell state and regulatory mechanisms.

Matched single-cell chromatin, transcriptome, and surface marker profiling captures in vivo epigenomic reprogramming during basal-to-luminal transition in the mammary gland

The paper introduces OneCell CUT&Tag, a single-cell multi-omics method that captures chromatin, transcriptome, and surface marker data, revealing epigenomic reprogramming during mammary gland basal-to-luminal transition.

Accurate Macromolecular Complex Modeling for Cryo-EM with CryoZeta

CryoZeta improves cryo-EM structure modeling by integrating density features with sequence data using a diffusion-based deep learning model, achieving higher accuracy than existing methods.