Identification and validation of potential diagnostic signature and immune cell infiltration for HIRI based on cuproptosis-related genes through bioinformatics analysis and machine learning.

Abstract

Authors

• Fang Xiao
  Department of Gastroenterology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
• Guozhen Huang
  Division of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
• Guandou Yuan
  Division of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
• Shuangjiang Li
  Division of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
• Yong Wang
  State Key Laboratory of Chemical Biology and Drug Discovery, Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University Hunghom Kowloon Hong Kong P. R. China kwok-yin.wong@polyu.edu.hk.
• Zhi Tan
  Graduate School, Woosuk University, Jeonju 514500, Republic of Korea.
• Zhipeng Liu
  Institute of Advanced Materials (IAM) & Key Laboratory of Flexible Electronics (KLOFE), Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM), Nanjing Tech University (NanjingTech), 30 South Puzhu Road, Nanjing 211816, PR China.
• Stephen Tomlinson
  Department of Microbiology and Immunology, Medical University of South Carolina, Charleston, SC, United States.
• Songqing He
  Division of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
• Guoqing Ouyang
  Division of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
• Yonglian Zeng
  Division of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.

Keywords

External Resources