Evaluation of triphenyl phosphate's pathogenic potential and molecular mechanisms in glioblastoma: an integrated network toxicology investigation employing multiple machine learning approaches.
Overview
- Graduate School, Ningxia Medical University, Yinchuan, China
- Master’s Training Station, General Hospital of Ningxia Medical University, Yinchuan, China
- Department of Radiation Oncology, General Hospital of Ningxia Medical University, Yinchuan, China
- Institute of Medical Sciences, General Hospital of Ningxia Medical University, Yinchuan, China
- Cancer Institute, General Hospital of Ningxia Medical University, Yinchuan, China
Abstract
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Data
Data links
- ncbi.nlm.nih.gov/
geo , NCBI; found in the text, “Data retrieval and download from Gene…”
Versions
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Version 1, 30 September 2026: the first record
Recorded: type, language, journal, volume, issue, pages, dates, 5 authors, 5 keywords, 34 references.
Cite
This paper
Wang, Z., Cui, K., Wang, J., Ma, R., & Wang, Y. (2026). Evaluation of triphenyl phosphate's pathogenic potential and molecular mechanisms in glioblastoma: an integrated network toxicology investigation employing multiple machine learning approaches. Translational cancer research, 15(3), 202. https://
BibTeX
@article{wang2026evaluat
author = {Wang, Ziyu and Cui, Kai and Wang, Jialin and Ma, Rong and Wang, Yanyang},
title = {{Evaluation of triphenyl phosphate's pathogenic potential and molecular mechanisms in glioblastoma: an integrated network toxicology investigation employing multiple machine learning approaches}},
journal = {Translational cancer research},
year = {2026},
month = mar,
volume = {15},
number = {3},
pages = {202},
publisher = {AME Publications},
issn = {2218-676X},
doi = {10.21037/
url = {https://
pmid = {41969433},
pmcid = {PMC13067006}
}
RIS
TY - JOUR
AU - Wang, Ziyu
AU - Cui, Kai
AU - Wang, Jialin
AU - Ma, Rong
AU - Wang, Yanyang
TI - Evaluation of triphenyl phosphate's pathogenic potential and molecular mechanisms in glioblastoma: an integrated network toxicology investigation employing multiple machine learning approaches
T2 - Translational cancer research
J2 - Transl Cancer Res
PY - 2026
DA - 2026/
VL - 15
IS - 3
SP - 202
SN - 2218-676X
PB - AME Publications
DO - 10.21037/
UR - https://
LA - en
ER -
CSL-JSON
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