Population Cohort-Validated PM<sub>2.5</sub>-Induced Gene Signatures: A Machine Learning Approach to Individual Exposure Prediction

Population Cohort-Validated PM<sub>2.5</sub>-Induced Gene Signatures: A Machine Learning Approach to Individual Exposure Prediction

Transcriptomic profiling has shown that exposure to PM<sub>2.5</sub>, a common air pollutant, can modulate gene expression, which has been linked to negative health effects and diseases. However, there are few population-based cohort studies on the association between PM<sub>2.5<...

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Bibliographic Details
Main Authors: Yu-Chung Wei, Wen-Chi Cheng, Pinpin Lin, Zhi-Yao Zhang, Chi-Hsien Chen, Chih-Da Wu, Yue Leon Guo, Hung-Jung Wang
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Toxics
Subjects:
PM<sub>2.5</sub>
transcriptomic profiling
biomarker
machine learning
predictive model
Online Access:https://www.mdpi.com/2305-6304/13/7/562
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