Pedro Gabriel Ferreira

GLESKit is a gene-centered system that synthesizes biomedical evidence by integrating multiple data types, achieving high report quality and performance in benchmark tasks.

This study shows that cigarette smoking causes molecular changes in tissues similar to aging, including inflammation, hypomethylation at enhancers, and hypermethylation at Polycomb target regions.

This paper introduces a distributed computing framework for privacy-preserving GWAS analysis using trusted execution environments to enhance security and scalability.

This study evaluates deep learning methods for predicting drug synergy in cancer by testing different architectures, data types, and feature selection strategies.

The paper quantifies protein levels across 32 human tissues and compares them to transcriptome data, revealing insights into post-transcriptional regulation and disease mechanisms.