Roland Eils

Evolution of SARS-CoV-2 reshapes upper airway immunity in children

This study uses single-cell transcriptomics to show that SARS-CoV-2 variants reshape pediatric upper-airway immunity differently from adults.

Beyond benchmarking: an expert-guided consensus approach to spatially aware clustering

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

An interpretable omnigenic neural network architecture for the human genome

The paper introduces an interpretable neural network architecture for genomic prediction, outperforming existing methods in disease risk prediction and capturing non-linear genetic interactions.

Aberrant brain-type neuronal programs in large-cell pancreatic neuroendocrine carcinoma

The paper identifies two neuroendocrine cell states in large-cell pancreatic neuroendocrine carcinoma using single-nucleus transcriptomics, revealing an aberrant brain-type neuronal program and a stress-responsive state.

The Human Pancreas Cell Atlas defines a healthy reference framework for disease contextualization and translational benchmarking

The paper constructs a healthy human pancreas reference atlas to contextualize disease states and benchmark models.

Nonlinear mixed-effect models and tailored parametrization schemes enables integration of single cell and bulk data

This paper presents a framework for integrating single-cell and bulk data using nonlinear mixed-effect models and tailored parameter estimation, improving parameter identifiability and prediction accuracy.

Atlas-scale spatially aware clustering with support for 3D and multimodal data using SpatialLeiden

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

2D, or not 2D? Investigating Vertical Signal Integrity of Tissue Slices

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

Generating Synthetic Task-based Brain Fingerprints for Population Neuroscience Using Deep Learning

The paper introduces DeepTaskGen, a deep learning method that generates synthetic task-based contrast maps from resting-state fMRI data, outperforming benchmarks and enabling biomarker development for cognitive tasks.

Latent plasticity of the human pancreas across development, health, and disease.

The paper constructs a single-cell multiomics atlas of the human pancreas across development, health, and T2D, identifying plastic cell states and lineage trajectories.

Long-read single-cell RNA sequencing uncovers cell-type specific transcript regulation in COVID-19

This study uses long-read single-cell RNA sequencing to identify cell-type specific alternative splicing changes in COVID-19 patients compared to healthy controls.

Rewired type I IFN signaling is linked to age-dependent differences in COVID-19

This study identifies age-related rewiring of type I IFN signaling in immune cells linked to increased inflammation and altered antibody responses in COVID-19.

Biologically Informed Variational Inference Enables Interpretable Cell Phenotyping and Discovery

NetworkVI integrates multi-omics data using a biologically informed variational autoencoder, enabling interpretable cell phenotyping and discovery of lineage-specific immune states.

SpatialLeiden - Spatially-aware Leiden clustering

SpatialLeiden integrates spatial embeddings into Leiden clustering to create a spatially aware method that performs well compared to existing spatial clustering techniques.

Sainsc: a computational tool for segmentation-free analysis of in-situ capture

Sainsc provides a segmentation-free tool for analyzing high-resolution spatial transcriptomics data, enabling accurate subcellular cell-type mapping with lower computational demands.

Dynamics of SARS-CoV-2 host cell interactions inferred from transcriptome analyses

This study uses time-resolved RNA sequencing and mathematical modeling to analyze SARS-CoV-2 host cell interactions, revealing transcriptional dynamics and identifying druggable host pathways.

Disturbed trophoblast transition links preeclampsia progression from placenta to the maternal syndrome

The paper identifies a disrupted trophoblast transition in preeclampsia, linking placental pathology to maternal syndrome through multi-omics profiling and in vitro analyses.

ELF5 is a respiratory epithelial cell-specific risk gene for severe COVID-19

This study identifies ELF5 as a risk gene for severe COVID-19 using genetic and single-cell expression data, showing its specific expression in respiratory epithelial cells.

Profibrotic priming of airway cell types and drug responses in early-stage idiopathic pulmonary fibrosis

This study uses early-stage IPF patient-derived cells to identify proinflammatory and fibrotic states and assess drug responses in airway cells.

SSAM-lite: a light-weight web app for rapid analysis of spatially resolved transcriptomics data

SSAM-lite provides a lightweight, web-based tool for rapid, segmentation-free analysis of spatially resolved transcriptomics data, enabling broad accessibility without requiring computational expertise.

Cell segmentation-free inference of cell types from in situ transcriptomics data

This paper introduces SSAM, a cell segmentation-free method for cell-type identification and tissue domain detection in in situ transcriptomics data, showing it detects known and discovers new cell types in mouse brain tissues.

Integrative Ranking Of Enhancer Networks Facilitates The Discovery Of Epigenetic Markers In Cancer

The paper introduces a computational tool to identify epigenetic markers in cancer by analyzing enhancer networks across epigenomic datasets.

Gene set inference from single-cell sequencing data using a hybrid of matrix factorization and variational autoencoders

The paper introduces a hybrid model combining matrix factorization and variational autoencoders to infer gene sets from scRNA-seq data, correcting batch effects and identifying cell types.

Olfactory transmucosal SARS-CoV-2 invasion as port of Central Nervous System entry in COVID-19 patients

The paper investigates SARS-CoV-2 entry into the CNS via the olfactory mucosa in COVID-19 patients and demonstrates neurotropism and cerebral thromboembolism.

Optogenetic control of Neisseria meningitidis Cas9 genome editing using an engineered, light-switchable anti-CRISPR protein

This paper introduces an optogenetic tool to control NmeCas9 activity using a light-switchable anti-CRISPR protein, enabling precise genome editing in mammalian cells.

Single nucleus and in situ RNA sequencing reveals cell topographies in the human pancreas

The paper uses single nucleus and in situ RNA sequencing to create a comprehensive atlas of human pancreas cells, revealing cell topographies and differences between adult and neonatal pancreata.

Framework For Quality Assessment Of Whole Genome, Cancer Sequences

The paper introduces a framework for assessing the quality of whole genome cancer sequences using a star rating system based on five QC measures, providing a tool for researchers to evaluate and exclude low-quality data.

The COVID-19 PHARMACOME: A method for the rational selection of drug repurposing candidates from multimodal knowledge harmonization

The paper presents a drug-target-mechanism graph to identify synergistic drug combinations for SARS-CoV-2 treatment, validated through experimental testing.

SARS-CoV-2 receptor ACE2 and TMPRSS2 are predominantly expressed in a transient secretory cell type in subsegmental bronchial branches

Single-cell profiling of lung and bronchial cells places ACE2 mainly in a transient secretory cell state of cultured bronchial epithelium, between goblet and ciliated cells, co-expressing TMPRSS2.

Computational design of anti-CRISPR proteins with improved inhibition potency and expanded specificity

The paper designs improved anti-CRISPR proteins with enhanced inhibition potency and expanded specificity through structure-based engineering.