Giusy del Giudice

The paper presents an AI workflow for mapping Key Events to genes in Adverse Outcome Pathways, improving accuracy and reducing manual effort through semantic retrieval, LLM refinement, and expert curation.

MUUMI integrates multi-omics data using statistical meta-analysis and network-based methods to identify robust molecular signatures and interactomes.

OpTiles dynamically defines tiling windows for methylation data based on CpG distribution and variability, improving reliability and annotation of targeted methylation datasets.

This study investigates how polarizing environments affect macrophage gene expression and DNA methylation, revealing long-term regulatory responses and common epigenetic changes across stimuli.

This paper develops a network-based toxicology approach to model nanomaterial hazard by linking molecular changes to adverse outcomes in biological systems.

This study integrates public transcriptomic data with network analysis to identify molecular features of psoriasis, revealing key genes and networks involved in the disease.