Simon Koplev

This paper creates a detailed heart atlas using multimodal data to identify cell states and disease-associated genetic variants in specific heart regions.

This study creates a spatial genomics atlas of human skin fibroblasts in health and disease, identifying six major populations and three disease-specific subtypes.

The paper maps the spatial organization of the human thymus across developmental stages using a multimodal atlas and identifies key cellular and molecular features of T cell development.

The paper integrates single-cell RNA-seq datasets across the GI tract to identify epithelial metaplasia in inflammatory diseases, showing its role in inflammation through immune cell interactions.

This study identifies shared and distinct genetic pathways between human and mouse in coronary artery disease using multi-omics data and GWAS, showing over 75% shared pathways.

This study uses transcriptome-wide association analysis to identify 114 genes associated with coronary artery disease, including 18 novel genes, and shows they are enriched in lipid metabolism pathways.

The paper introduces a Bayesian method to estimate protein concentrations and phosphorylation site occupancy ratios from mass spectrometry data, applied to study PRKAR1A-RET gene fusion effects.

This paper introduces nTEP barcoding to spatially resolve tumour clones and their interactions with the microenvironment using multiplexed antibody imaging.