Luz García‐Alonso

This study uses spatial transcriptomics to map gene expression gradients in the human endometrium, revealing coordinated regeneration and niche architecture during menstrual breakdown.

This paper creates an integrated multimodal atlas of the female reproductive system across the lifespan, identifying cell types and linking them to gynaecological pathologies.

This study creates a comprehensive spatial atlas of the human ovarian cortex, revealing molecular mechanisms of primordial follicle activation and follicle niche organization.

This study creates a single-cell multiomics atlas of B cell development in prenatal and adult bone marrow and in vitro models, identifying novel cell subsets and molecular signatures.

The paper introduces scCellFie, a framework to infer metabolic activities from single-cell and spatial transcriptomics data, revealing organ-specific metabolic programs and disease-associated alterations.

This study creates a single-cell spatial atlas of the developing human reproductive tract, identifying genes and mechanisms involved in sexual dimorphism and organ development.

The paper constructs a high-resolution single-cell reference atlas of the human endometrium, identifying cell types, states, and signaling networks, and links them to endometriosis.

This study creates a spatially resolved single-cell multiomics atlas of human trophoblast differentiation in early pregnancy, revealing key regulatory programs and cell-cell communication events involved in EVT invasion and arterial transformation.

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.

The paper creates a comprehensive human phosphoproteome by integrating 6,801 phospho-enriched mass spectrometry experiments and prioritizes functional phosphosites using machine learning.

The paper benchmarks and integrates TF regulon resources to assess their impact on TF activity estimation in human gene expression data.

The paper develops SLAPenrich to analyze pathway alterations in cancer hallmarks across 4,415 patients, revealing hallmark predominance and suggesting novel driver genes.

The paper analyzes proteogenomic data to show that chromosomal rearrangements often reduce protein abundance post-transcriptionally, particularly in protein complexes, and identifies regulatory interactions linked to drug resistance.

This paper describes a method to identify drug resistance mutations in cancer using genome-wide chemical mutagenesis and next-generation sequencing, enabling the discovery of both known and novel resistance mechanisms.