Michele Fratello

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.

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

This paper maps disease relationships using six data dimensions to reveal novel insights beyond traditional classifications, identifying shared features between Type 2 diabetes and Alzheimer's disease.

This paper introduces a method using clustering and stochastic rank aggregation to identify functional neuromarkers in resting-state fMRI data, finding distinct parcel rankings between healthy controls and patients with Parkinson's disease and amyotrophic lateral sclerosis.