Simon Mages

SCOTE quantifies spatial relationships across all length scales in spatial omics data, revealing biological insights while distinguishing platform artifacts.

The paper identifies sequence variation in 5S rRNA genes across human populations and shows that variants disrupting ribosome assembly activate p53 and are selected against.

scDynOmics is a transformer model for single-cell multiomics data that outperforms existing models and provides interpretable insights into cellular dynamics.

This paper benchmarks 26 spatial domain detection methods across real and semi-synthetic spatial transcriptomics data to identify performance drivers and introduce a modular benchmarking framework.

This study identifies truncating RELA variants causing autoinflammation and autoimmunity by disrupting NF-κB feedback control and immune homeostasis.

This paper introduces a FACS-based preprocessing workflow for PBMCs that improves scRNA-seq throughput and preserves biological integrity while enabling rare cell enrichment and cross-donor multiplexing.

SlideCNA detects spatial copy number alterations from Slide-seq data to identify sub-clones in metastatic breast cancer.

The paper develops a computational framework to study division of labor in tissues by analyzing cell interactions and spatial cues using single-cell RNA-seq and spatial transcriptomics data.

TACCO is a framework for annotating cell identities in single-cell and spatial omics data, excelling in speed and performance across datasets.

SM-Omics is a platform that combines spatial transcriptomics and proteomics to analyze tissue samples at scale.