Mercedes Jimenez‐Liñan

This study infers somatic copy number aberrations from spatial transcriptomics data to identify spatially coherent SCNA-defined populations in early cancer development.

This study maps the temporal and spatial dynamics of the human endometrium using single-cell and spatial reference maps, identifying key signaling pathways regulating cell fate in vivo and in vitro.

This paper uses deep transfer learning on H&E images to correlate histopathological patterns with genomic and survival data across 28 cancer types, revealing associations between histopathology and molecular features.

The paper shows that selecting short DNA fragments in plasma improves the detection of circulating tumour DNA by enriching mutated DNA, enabling identification of copy number alterations previously undetected.