Deep learning identified glioblastoma subtypes based on internal genomic expression ranks.

Journal: BMC cancer
Published Date: Jan 20, 2022

Abstract

BACKGROUND: Glioblastoma (GBM) can be divided into subtypes according to their genomic features, including Proneural (PN), Neural (NE), Classical (CL) and Mesenchymal (ME). However, it is a difficult task to unify various genomic expression profiles which were standardized with various procedures from different studies and to manually classify a given GBM sample into a subtype.

Authors

  • Xing-Gang Mao
    Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi Province, People's Republic of China.
  • Xiao-Yan Xue
    Department of Pharmacology, School of Pharmacy, Fourth Military Medical University, Xi'an, Shaanxi Province, People's Republic of China.
  • Ling Wang
    The State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, #7 Jinsui Road, Guangzhou, Guangdong 510230, China.
  • Wei Lin
    Department of Geriatric Rehabilitation, Jiangbin Hospital, Nanning, China.
  • Xiang Zhang
    Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, Sichuan, China.

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