Machine Learning Hunt Uncovers Three Molecular Culprits Behind Toxic Herb Kidney Disease
A combined network toxicology, machine learning, and experimental study has identified FABP3, PDE4B, and SLC1A3 as core candidate targets underlying ...
A combined network toxicology, machine learning, and experimental study has identified FABP3, PDE4B, and SLC1A3 as core candidate targets underlying ...
A new computational study links the common cosmetic preservative methylparaben to five key breast cancer signaling proteins and unveils a ...
An integrated multiomics and machine learning study has identified SERPING1 as a leading candidate biomarker for amiodarone-induced pulmonary fibrosis, with ...
A new investigation traces a fatal family poisoning in China to Datura stramonium seedlings mistaken for edible wild vegetables, combining ...
A network toxicology and machine learning study identifies four genes through which the environmental carcinogen benzopyrene may drive prostate cancer ...
An integrated study combining NHANES epidemiology, machine learning, single-cell transcriptomics, molecular docking, and mouse experiments links background-level PFOS exposure to ...
© 2025 Scienmag - Science Magazine
© 2025 Scienmag - Science Magazine