Glioma stages prediction based on machine learning algorithm combined with protein-protein interaction networks.

Journal: Genomics
Published Date: May 29, 2019

Abstract

BACKGROUND: Glioma is the most lethal nervous system cancer. Recent studies have made great efforts to study the occurrence and development of glioma, but the molecular mechanisms are still unclear. This study was designed to reveal the molecular mechanisms of glioma based on protein-protein interaction network combined with machine learning methods. Key differentially expressed genes (DEGs) were screened and selected by using the protein-protein interaction (PPI) networks.

Authors

  • Bing Niu
    College of Life Science, Shanghai University, 99 Shang-Da Road, Shanghai 200444, China.
  • Chaofeng Liang
    Department of Neurosurgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Yi Lu
    Department of Gastrointestinal Endoscopy, The Sixth Affiliated Hospital, Sun Yat-Sen University, 26th Yuancun the Second Road, Guangzhou, 510655, Guangdong Province, China.
  • Manman Zhao
    College of Life Science, Shanghai University, 99 Shang-Da Road, Shanghai 200444, China.
  • Qin Chen
    School of Life Sciences, Shanghai University, Shanghai 200444, China. Electronic address: chenqincc@edu.cn.
  • Yuhui Zhang
    Department of Mathematical and Computing Science, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo, 152-8550, Japan. Electronic address: zhang.y.av@m.titech.ac.jp.
  • Linfeng Zheng
    Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China; Department of Radiology, Shanghai First People's Hospital, Baoshan Branch, Shanghai 200940, China. Electronic address: zhenglinfeng04@aliyun.com.
  • Kuo-Chen Chou
    School of Computer Science and Technology and Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong 518055, China, Gordon Life Science Institute, Belmont, MA 02478, USA and Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, 21589, Saudi Arabia School of Computer Science and Technology and Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong 518055, China, Gordon Life Science Institute, Belmont, MA 02478, USA and Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, 21589, Saudi Arabia.

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