Christoph Kuppe

AtlasOT improves multimodal integration of disease atlases by addressing unpaired data constraints through a novel optimal transport framework.

The paper uses single-cell RNA sequencing to analyze PDL cells from maxilla and mandible pairs, finding uniform mesenchymal populations with donor-specific substates and limited jaw-related transcriptional differences.

The paper introduces SACCELERATOR, a framework for spatially aware clustering that improves benchmarking by incorporating expert feedback and consensus analysis across diverse datasets.

IntraTalker+CrossTalkeR models intracellular and intercellular signaling in single-cell data to uncover cell-state changes and novel signaling roles.

The paper shows that reversing PROTAC-induced ASH2L degradation restores H3K4me3, gene expression, and proliferation in senescent cells.

The paper extends SpatialLeiden to handle atlas-scale, 3D, and multimodal spatial omics data, improving modularity and scalability across multiple samples.

This study identifies polyploid cardiomyocytes as disease-specific transcriptional states in the mammalian heart and suggests targeting them for heart failure treatment.

This paper introduces a tool to detect overlapping cells and segmentation errors in 3D spatial transcriptomics data.

Single-cell and spatial maps of human coronary arteries identify FAP as a marker of SMC-derived modulated cells; an anti-FAP BiTE reduced plaque burden in mouse models.

The paper identifies a neonatal liver program that expands regulatory T cells while limiting conventional T cell activation, influencing susceptibility to viral infections and protection against liver disease.

This study identifies vascular niches as key hotspots for age-related inflammation and fibrosis in cardiac tissue using single-nucleus RNA sequencing and spatial transcriptomics.

PILOT-GM-VAE analyzes single cell disease atlases to perform sample-level clustering, trajectory inference, and batch correction using Gaussian Mixture Variational Autoencoders with optimal transport.

This study investigates the postnatal maturation of the small intestinal epithelium, identifying developmental regulators as key drivers over microbiota effects.

The paper develops single-cell damage scores to quantify cellular deterioration in degenerative diseases and applies them to murine and human datasets to identify molecular trajectories of damage.

PHLOWER infers complex differentiation trees from multi-modal single-cell data using Hodge Laplacian decomposition, showing effectiveness in kidney organoid data.

PILOT uses optimal transport to analyze single-cell and pathomics data, detecting disease-associated samples and non-linear changes in cell populations and tissue structures.

scMEGA infers gene regulatory networks from single-cell multi-omics data, demonstrating its application in studying myofibroblast activation in human myocardial infarction.

The paper defines the cellular and transcriptional features of cardiac recovery using snRNA-seq, identifying RUNX1 downregulation as a key predictor and potential therapeutic target.

This study generates a high-resolution spatial multi-omic map of human myocardial infarction by integrating single-cell gene expression, chromatin accessibility, and spatial transcriptomic data to reveal cellular zones of injury, repair, and remodeling.

This study uses human pluripotent stem cell-derived kidney organoids to model nephrotic syndrome, showing they can replicate podocyte injury and respond to genetic correction.

scOpen improves downstream analysis of sparse scATAC-seq data by imputing open chromatin regions, revealing regulatory changes in kidney fibrosis.

COSMOS integrates multi-omics data with prior knowledge to generate mechanistic hypotheses about biological processes in renal cell carcinoma.