Santiago García‐Martín

The paper presents a pan-cancer single-cell atlas linking intratumoral states to therapeutic vulnerabilities by integrating transcriptomics, copy-number alterations, and drug-response predictions across 34 tumor types.

This paper uses single-cell transcriptomics to identify drug response subgroups and therapeutic targets in endometriosis, revealing tissue-specific and inter-patient heterogeneity.

This study uses spatial transcriptomics to analyze drug responses in breast cancer tumors and identifies therapeutic heterogeneity linked to tumor location and microenvironment.

Beyondcell identifies drug-responsive subpopulations in single-cell RNA-seq data and proposes cancer-specific treatments by analyzing therapeutic clusters and differential drug sensitivity.

DREIMT prioritizes immunomodulatory drugs by analyzing gene expression signatures and drug profiles.