Vanessa Smer-Barreto

This study screens a large compound library across patient-derived GBM stem cells to identify effective drugs targeting tumor heterogeneity and presents validated hits for further exploration.

This study identifies three compounds targeting glioblastoma stem cells using machine learning and high-throughput screening of patient-derived models.

The paper systematically explores RNA-ligand interactions by analyzing mutations in an RNA aptamer, revealing complex phenotypic effects and training a model to predict RNA structure from epistasis.