Integrated multi-omics, machine learning, network toxicology, and molecular docking reveal potential mechanisms underlying methyl 4-hydroxybenzoate-associated breast cancer.

Multi-omics, machine learning, and molecular simulation identify CD44 as a candidate target in endocrine-disrupting chemical-associated thyroid cancer progression.

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 experimenta...

Integrated multi-omics and experimental analyses reveal VIPR1 as a potential mediator linking environmental bisphenol A exposure to MASH-HCC progression.

Findings identify a VIPR1-centered molecular vulnerability linking BPA exposure with malignant-associated alterations under lipotoxic conditions and provide candidate biomarkers and therapeutic targets for further investigation.

Integrated Transcriptomic, Network Pharmacology, and Machine-Learning Framework Identifies Candidate Phytochemical-Associated Targets in Lung Adenocarcinoma

CA4 is prioritized as a reproducible LUAD-associated candidate supported by transcriptomic, machine-learning, immune, survival, and docking evidence, but the computational findings do not demonstrate direct phytochemical regulation of CA4 or therapeutic efficacy.

Network toxicology-aided identification of potential toxicological mechanisms of rhodamine B in ovarian cancer: Insights from transcriptomics, molecular docking, molecular dynamics simulations, and machine learning modeling

Rhodamine B is suggested as a multi-target toxic agent, potentially disrupting apoptotic and invasive signaling associated with ovarian cancer, consistent with machine learning predictions indicating inactivity against the Caov-3 ovarian cancer cell line.

An integrated network toxicology and multi-omics framework prioritizes BRCA1 as a testable candidate in benzo[a]pyrene-associated oral cancer

The current findings do not establish direct BaP–BRCA1 binding, direct regulation of BRCA1 by BaP, a definitive in vivo mechanism, or clinical causality, and require further validation through direct biochemical assays, additional experimental models, and exposure-annotated human cohorts.