Identification of diagnostic genes and the miRNA‒mRNA‒TF regulatory network in human oocyte aging via machine learning methods.

Journal: Journal of assisted reproduction and genetics
PMID: 39540991

Abstract

PURPOSE: Oocyte aging is a significant factor in the negative reproductive outcomes of older women. However, the pathogenesis of oocyte aging remains unclear. This study aimed to identify the hub genes involved in oocyte aging via bioinformatics methods.

Authors

  • Xi Luo
    Department of Stomatology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
  • Mingming Liang
    State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China. Electronic address: liangmingming2015@ia.ac.cn.
  • Dandan Zhang
    College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua, China.
  • Ben Huang
    State Key Laboratory of Conservation and Untilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China.

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