Article
A Predictive Framework Integrating Network Toxicology and Machine Learning Elucidates 6PPD-Quinone-Induced Glioblastoma Pathogenesis
2026-02-19
Abstract excerpt
<title>Abstract</title> <p>Through machine learning analysis, we identified five core genes with special diagnostic performance, namely SCN2B, VIPR1, PAK1, MAP2K1 and SYNJ1. The AUC value of this integrated model in the validation queue reached 0.957, and its prediction accuracy is relatively high. From the analysis of SHAP interpretability, it can be found that MAP2K1 is the most influential predictor, and there...
Topics
Open a Topic to create a Post that cites this publication.
Identifiers and source
- Literature Corpus work
- 375d232c-111a-52f2-a50b-b872ab784f4b
- DOI
- 10.21203/rs.3.rs-8679784/v1
