Garry P. Nolan

Quantum Barcoding Bridges High-Dimensional Immune Phenotyping with Signaling Responses across Species

The paper benchmarks Quantum Barcoding against mass cytometry in human and rhesus macaque blood, integrating data to reveal conserved and divergent signaling responses across species.

Single-cell profiling reveals stromal niche and α5β1 regulation of neutrophil phenotypes in ulcerative colitis

This study uses single-cell RNA sequencing and spatial profiling to show fibroblasts influence neutrophil inflammation in UC, with 5β1 targeting reducing inflammatory responses.

Fault-tolerant 3D reconstruction from 2D spatial proteomics sections

This paper introduces 3D-Omics-Flow, a method that reconstructs 3D molecular volumes from 2D spatial proteomics sections by repairing damaged sections and interpolating between them.

Coordinated immune-epithelial dynamics in the nasal epithelium protect against respiratory virus infection

The paper identifies IL13-driven immune-epithelial remodeling in the nasal epithelium that restricts respiratory virus infection by reshaping the mucus barrier.

Immune Checkpoint Therapy Drives Maturation of a Cellular Neighborhood Nucleated by T Cell-APC Triads Enabling Spatially Compartmentalized Tumor Immunity

The paper uses multiplex imaging to track the development of T cell-APC triad neighborhoods during immune checkpoint therapy, showing their role in spatially organizing tumor immunity.

Epstein-Barr Virus Orchestrates Spatial Reorganization and Immunomodulation within the Classic Hodgkin Lymphoma Tumor Microenvironment

This study uses spatial multi-omics to compare EBV-positive and EBV-negative cHL, identifying distinct TME features and immunological signatures linked to EBV.

Spatial immune hubs defined by conserved activated dendritic cells are remodeled by immunotherapy

The paper constructs an integrated atlas of tumor-infiltrating dendritic cells across species and immunotherapy conditions, revealing conserved activation states and spatial reorganization in response to therapy.

SPACEc: A Streamlined, Interactive Python Workflow for Multiplexed Image Processing and Analysis

SPACEc provides a Python workflow for analyzing multiplexed imaging data with interactive tools for image processing, segmentation, and spatial analysis.

Fluid-Squid: DIY Multiplexed Imaging of Cells and Tissues

Fluid-Squid enables customizable, cost-effective multiplexed imaging of cells and tissues through automated fluidics and barcoding strategies.

High-Dimensional Spatiotemporal Single-Cell and 3D Atlas of the Bone Marrow Microenvironment during Leukemic Progression

This study maps the spatiotemporal changes in the bone marrow microenvironment during CML progression using single-cell and 3D imaging, revealing immune evasion and niche disruption.

Alterations of the composition and spatial organization of the microenvironment following non-dysplastic Barrett's esophagus through progression to cancer

This study identifies immune cell changes and gene expression patterns in Barrett's esophagus progression to cancer using spatial and multi-omic analyses.

Spatially organized inflammatory myeloid-CD8+ T cell aggregates linked to Merkel-cell Polyomavirus driven Reorganization of the Tumor Microenvironment

The paper identifies spatial immune patterns in Merkel cell carcinoma linked to viral status and patient outcomes.

MONTAGE: A Computation Framework to Identify Spatially Resolved Functional Enrichment Gradients in the Tissue Microenvironment via Spatial Communities

MONTAGE identifies spatially resolved functional enrichment gradients in tumor microenvironments by analyzing spatial communities and their clinical relevance.

Natural Killer Cell Receptor Signaling and Activation Depend on Cell Cycle Stages

This study shows that NK cell receptor signaling and activation vary with cell cycle stages, with some proteins showing non-monotonic abundance changes.

A Spatial Multi-Modal Dissection of Host-Microbiome Interactions within the Colitis Tissue Microenvironment

This study introduces MicroCart, a framework for spatial multi-omics analysis of host-microbiome interactions in colitis, revealing tissue-level immune responses and microbial shifts.

The tidyomics ecosystem: Enhancing omic data analyses

The paper introduces tidyomics, an ecosystem bridging Bioconductor and tidy R to streamline omic analysis using data from the Human Cell Atlas.

Cross-domain information fusion for enhanced cell population delineation in single-cell spatial-omics data

This paper introduces CellSNAP, a self-supervised method that integrates spatial, transcriptomic, and proteomic data to improve cell population delineation in spatial-omics datasets.

Integrating Multiplexed Imaging and Multiscale Modeling Identifies Tumor Phenotype Transformation as a Critical Component of Therapeutic T Cell Efficacy

The paper integrates multiplexed imaging and multiscale modeling to show that T cell phenotype influences tumor phenotype conversion, critical for therapeutic efficacy.

Integration of spatial and single-cell data across modalities with weak linkage

The paper introduces MaxFuse, a method for integrating spatial and single-cell omics data with weak linkage, demonstrating its effectiveness in consolidating proteomic, transcriptomic, and epigenomic information.

Robust Single-cell Matching and Multi-modalAnalysis Using Shared and Distinct FeaturesReveals Orchestrated Immune Responses

The paper introduces MARIO, a cell matching algorithm that integrates single-cell proteomic and multi-modal data, revealing orchestrated immune responses in lung tissue.

Spatial omics representation and functional tissue module inference using graph Fourier transform

This paper introduces SpaGFT, a graph Fourier transform model for spatial omics data analysis, enabling accurate identification of tissue modules and their functional relationships in spatial transcriptomics and proteomics data.

Annotation of Spatially Resolved Single-cell Data with STELLAR

STELLAR annotates spatially resolved single-cell data using geometric deep learning, discovering cell types and states while transferring annotations across tissues and donors.

Identification of cell types in multiplexed in situ images by combining protein expression and spatial information using CELESTA reveals novel spatial biology

CELESTA identifies cell types in multiplexed in situ images by integrating protein expression and spatial information, revealing novel spatial biology associated with lymph node metastasis.

High Resolution Single Cell Maps Reveals Distinct Cell Organization and Function Across Different Regions of the Human Intestine

The paper maps cell organization and function across human intestine regions using single nuclear RNA and open chromatin assays, revealing distinct cell neighborhoods and regulatory differences.

Integration of Mechanistic Immunological Knowledge into a Machine Learning Pipeline Increases Predictive Power

The paper introduces a machine learning method that integrates immunological knowledge to improve predictive power from mass cytometry data.

Subcellular localization of drug distribution by super-resolution ion beam imaging

The paper introduces srIBI, a super-resolution imaging technique, to visualize subcellular localization of biomolecules and drugs at the nanometer scale.

Ion beam subcellular tomography

This paper introduces ion beam tomography (IBT), a 3D subcellular imaging technique, and demonstrates its ability to visualize genomic regions, RNA transcripts, and protein factors with high resolution.

Deep profiling of mouse splenic architecture with CODEX multiplexed imaging.

The paper uses CODEX multiplexed imaging to analyze mouse spleen architecture, revealing how cellular neighborhoods affect immune cell receptor expression and identifying altered cell interactions in lupus.

Meta-analysis of Cytometry Data Reveals Racial Differences in Immune Cells

MetaCyto enables meta-analysis of flow and mass cytometry data, revealing racial differences in immune cell populations across 2926 samples.

Continuous visualization of differences between biological conditions in single-cell data

The paper introduces a tool for visualizing differences between biological conditions in single-cell data using overlapping KNN groupings, improving upon traditional partition-based methods.