Mining phase separation-related diagnostic biomarkers for endometriosis through WGCNA and multiple machine learning techniques: a retrospective and nomogram study.

Journal: Journal of assisted reproduction and genetics
PMID:

Abstract

OBJECTIVE: The objective of this study was to investigate the role of phase separation-related genes in the development of endometriosis (EMs) and to identify potential characteristic genes associated with the condition.

Authors

  • Qiuyi Liang
    Computational Medicine and Epidemiology Laboratory (CMEL), The Marine Biomedical Research Institute of Guangdong Zhanjiang, School of Ocean and Tropical Medicine, Guangdong Medical University, Zhanjiang, China.
  • Shengmei Yang
    Obstetrical Department, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Meiyi Mai
    Computational Medicine and Epidemiology Laboratory (CMEL), The Marine Biomedical Research Institute of Guangdong Zhanjiang, School of Ocean and Tropical Medicine, Guangdong Medical University, Zhanjiang, China.
  • Xiurong Chen
    Computational Medicine and Epidemiology Laboratory (CMEL), The Marine Biomedical Research Institute of Guangdong Zhanjiang, School of Ocean and Tropical Medicine, Guangdong Medical University, Zhanjiang, China.
  • Xiao Zhu
    Southern Marine Science and Engineering Guangdong Laboratory Zhanjiang, The Marine Medical Research Institute of Guangdong Zhanjiang (GDZJMMRI), Guangdong Medical University, Zhanjiang, China. Electronic address: xzhu@gdmu.edu.cn.