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

Journal: Cell biology and toxicology
PMID: 39707003

Abstract

BACKGROUND: Globally, pre-eclampsia (PE) poses a major threat to the health and survival of pregnant women and fetuses, contributing significantly to morbidity and mortality. Recent studies suggest a pathological link between PE and ferroptosis. We aim to utilize non-negative matrix factorization (NMF) clustering and machine learning algorithms to pinpoint disease-specific genes related to the process of ferroptosis in PE and investigate likely underlying biochemistry mechanisms.

Authors

  • Xuemin Liu
    National Engineering Research Centre for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou 510006, P. R. China.
  • Di Zhang
    College of Food Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
  • Hui Qiu
    Department of Emergency Surgery, The west campus of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

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