Marc Subirana-Granés

The paper investigates whether common cis-eQTLs explain gene expression deviations from ploidy expectations in Down syndrome using transcriptomic data from the Human Trisome Project and GTEx.

The paper introduces a section-aware RAG system for Down syndrome research that prioritizes experimental results to generate accurate, cited responses.

CCC-GPU provides a GPU-accelerated nonlinear correlation coefficient for large-scale transcriptomic data, improving speed and detecting nonlinear relationships.

This study integrates transcriptomic and genetic data to identify molecular signatures and potential biomarkers for Down syndrome comorbidities.

CLAMP integrates genetic associations and drug signatures with large-scale RNA-seq data to identify interpretable gene modules linked to complex diseases.

This study compares immunotherapy responses in subcutaneous and orthotopic dMMR LUAD models, finding that orthotopic models show better anti-PD1 response with increased immune infiltration and CD4+ memory T cells.

This study identifies noncoding regulatory regions and their mutations in insulinomas, linking them to altered β-cell function and tumor development.

This study shows that pro-inflammatory cytokines reveal plasticity in β-cell regulatory landscapes and identify T1D-associated variants disrupting cytokine-responsive enhancers.