Claudia Cava

MAVISp provides a modular structural framework for analyzing protein variant effects, offering over eight million variants across 1000 proteins with curated data and a web server for accessibility.

This study identifies 46 genetically correlated traits with ALS using GWAS data and performs causal inference, finding bidirectional genetic effects on several traits.

The paper identifies miRNA clusters driving triple negative breast cancer subtypes using a new computational pipeline and validates their role in promoting the phenotype through proliferation and EMT control.

Moonlight identifies cancer driver genes and their roles by integrating functional analysis and gene regulatory networks from expression data, distinguishing tumor suppressors, oncogenes, and moonlight genes.