Open access
Aug 2026
A network toxicology and machine learning approach to uncover the molecular machinery of bisphenol A-induced colorectal cancer
The machine learning-derived 12-gene signature, interpreted as CRC-associated genes overlapping with predicted BPA targets and supported by in silico molecular docking, offers valuable insights into the molecular basis of BPA-associated colorectal carcinogenesis and presents candidate targets for subsequent experimental validation.
Xiaoxuan Li, Genning Mai, Yuexi Xiao et al.
· Scientific Reports · 0 citations