Identification of potential biomarkers and mechanisms for keloid disorder based on comprehensive bioinformatics analysis and machine learning algorithms.

Journal: BMC medical genomics
Published Date: Jul 1, 2025

Abstract

BACKGROUND: Keloid disorder (KD) encompasses a spectrum of fibroproliferative dermal conditions, the pathogenesis remains complex and incompletely understood. This study sought to identify biomarkers and potential therapeutic targets for KD through an integrative bioinformatics approach and machine learning analysis of RNA sequencing data.

Authors

  • Bowen Zheng
    Department of Mechanical Engineering, University of California, Berkeley, CA, 94720, USA.
  • Jianxiong Qiao
    Department of Plastic Surgery, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, Gansu, 730030, China.
  • Xiaoping Yu
    Department of Radiology, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital, Changsha, Hunan, China.
  • Hanghang Zhou
    Department of Plastic Surgery, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, Gansu, 730030, China.
  • Anqi Wang
    Department of Colorectal Surgery, Changzheng Hospital, Navy Medical University, China.
  • Xuanfen Zhang
    Department of Plastic Surgery, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, Gansu, 730030, China. zhxf9304@126.com.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals