NMF typing and machine learning algorithm-based exploration of preeclampsia-related mechanisms on ferroptosis signature genes

This analytical journey illuminated a critical regulatory nexus in PE, underscoring the central influence of ARID3A on PE through ferroptosis-mediated pathways.

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Publication Details

Journal
Cell Biology and Toxicology
Published
2024-12-21
DOI
https://doi.org/10.1007/s10565-024-09963-5
Citations
5
Primary Topic
Pregnancy and preeclampsia studies
Type
article
Field-Weighted Citation Impact
2.91
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article

NMF typing and machine learning algorithm-based exploration of preeclampsia-related mechanisms on ferroptosis signature genes

Xuemin Liu, Di Zhang, Hui Qiu
5 citations
Cell Biology and Toxicology
Pregnancy and preeclampsia studies
2.91
article

NMF typing and machine learning algorithm-based exploration of preeclampsia-related mechanisms on ferroptosis signature genes

Xuemin Liu, Di Zhang, Hui Qiu
article en
5 citations

Abstract

This analytical journey illuminated a critical regulatory nexus in PE, underscoring the central influence of ARID3A on PE through ferroptosis-mediated pathways.

Cell Biology and ToxicologyVol. 41(1)
China Medical University (CN)
Openalex Percentile: Top 8%
Pregnancy and preeclampsia studies
2.91
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NMF typing and machine learning algorithm-based exploration of preeclampsia-related mechanisms on ferroptosis signature genes — Xuemin Liu, Di Zhang, et al. · Cell Biology and Toxicology (2024) | TGRS Research Map | TGRS