Identification of crucial genes for polycystic ovary syndrome and atherosclerosis through comprehensive bioinformatics analysis and machine learning.

Journal: International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Published Date: Feb 21, 2025

Abstract

OBJECTIVE: To identify potential biomarkers in patients with polycystic ovary syndrome (PCOS) and atherosclerosis, and to explore the common pathologic mechanisms between these two diseases in response to the increased risk of cardiovascular diseases in patients with PCOS.

Authors

  • Lirong Wang
    Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA; NIDA National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, PA 15261, USA; Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA. Electronic address: liw30@pitt.edu.
  • Yanli Zhang
    School of Information Science and Engineering, Shandong University, Jinan 250100, P. R. China.
  • Fan Ji
    School of Artificial Intelligence, Zhoukou Normal University, Zhoukou, Henan, China.
  • Zhenmin Si
    The First Clinical Medical College, Heilongjiang University of Chinese Medicine, Harbin, China.
  • Chengdong Liu
    Department of Traditional Chinese Medicine, Affiliated Hospital of Jiangsu University, Zhenjiang, China.
  • Xiaoke Wu
    The First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China.
  • Chichiu Wang
    Department of Obstetrics and Gynecology, The Chinese University of Hong Kong, Hong Kong, China.
  • Hui Chang
    Department of Thoracic Surgery, No. 153 Hospital of Liberation Army, Zhengzhou, China.

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