Beatriz Urda-García

EBEx prioritizes disease-relevant genes from transcriptomic data in COPD by integrating data-driven signals with curated gene sets and network-based expansion, identifying biologically relevant candidates and molecular subgroups.

The paper disentangles genetic and non-genetic factors contributing to disease co-occurrences using RNA-seq, heritability data, and UK Biobank genomic data.

The paper develops a method to generate a disease network using RNA-seq data, revealing molecular mechanisms behind comorbidities and identifying new associations through patient stratification.

This study uses synthetic data generation and explainable AI to uncover an intermediate subgroup in medulloblastoma, highlighting treatment disparities and supporting the continuum hypothesis between Groups 3 and 4.