An integrative omics-machine learning framework for predicting pulmonary responses to titanium dioxide nanoparticles
Abstract
-NP attributes to system-level transcriptomic response. By replacing hundreds of gene-specific models with a single, validated endpoint, this workflow streamlines omics-driven screening, potency ranking, and study-internal extrapolation in regulatory-relevant NAM pipelines.
Fields of Study & Subjects
Nanoparticles: synthesis and applications
Immunotoxicology and immune responses
Occupational and environmental lung diseases
Publication details
- Journal / source
- Nanoscale
- Volume
- 18
- Issue
- 13
- Pages
- 7021–7033
- Publication date
- 1 January 2026
- Language
- EN