HL-BscPF: Hybrid learning facilitates brain cell auto-identification in multiple pathologies.

Journal: Life sciences
Published Date: May 23, 2025

Abstract

AIMS: The rapidly growing scale and complexity of single-cell transcriptomic data in brain research make it increasingly difficult for traditional methods to extract meaningful insights efficiently, highlighting the need for artificial intelligence.

Authors

  • Zizheng Suo
    Department of anesthesiology, National Cancer Center / National Clinical Research Center for Cancer / Cancer hospital, Chinese Academy of Medical Sciences and Peking union medical college, Beijing 100021, PR China.
  • Bocheng Pan
    Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China.
  • Hailong Shi
    Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China.
  • Linhui Ma
    Department of anesthesiology, National Cancer Center / National Clinical Research Center for Cancer / Cancer hospital, Chinese Academy of Medical Sciences and Peking union medical college, Beijing 100021, PR China.
  • Yuxiang Zheng
    Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China.
  • Wenjie Xu
    Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
  • Lina Lin
    Department of anesthesiology, National Cancer Center / National Clinical Research Center for Cancer / Cancer hospital, Chinese Academy of Medical Sciences and Peking union medical college, Beijing 100021, PR China.
  • Enze Zhang
    High Performance Computer Research Center, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
  • Lijuan Wang
    HBISolutions Inc., Palo Alto, CA 94301, USA.
  • Mingzhu Zhang
    Department of anesthesiology, National Cancer Center / National Clinical Research Center for Cancer / Cancer hospital, Chinese Academy of Medical Sciences and Peking union medical college, Beijing 100021, PR China.
  • Yinyin Qu
    Department of Anesthesiology, Peking University Third Hospital, Beijing 100191, PR China.
  • Hui Zheng
    Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China.
  • Xingyu Gao
    Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China.
  • Cheng Ni
    Department of anesthesiology, National Cancer Center / National Clinical Research Center for Cancer / Cancer hospital, Chinese Academy of Medical Sciences and Peking union medical college, Beijing 100021, PR China. Electronic address: nicheng@cicams.ac.cn.

Keywords

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