MSpectraAI: a powerful platform for deciphering proteome profiling of multi-tumor mass spectrometry data by using deep neural networks.

Journal: BMC bioinformatics
Published Date: Oct 7, 2020

Abstract

BACKGROUND: Mass spectrometry (MS) has become a promising analytical technique to acquire proteomics information for the characterization of biological samples. Nevertheless, most studies focus on the final proteins identified through a suite of algorithms by using partial MS spectra to compare with the sequence database, while the pattern recognition and classification of raw mass-spectrometric data remain unresolved.

Authors

  • Shisheng Wang
    Liver Surgery and NHC Key Lab of Transplant Engineering and Immunology, Regenerative Medical Research Center, Department of Clinical Research Management, West China Hospital, Sichuan University, Chengdu 610041, China.
  • Hongwen Zhu
    Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China.
  • Hu Zhou
    Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China.
  • Jingqiu Cheng
    West China-Washington Mitochondria and Metabolism Research Center; Key Lab of Transplant Engineering and Immu-Nology, MOH, Regenerative Medicine Research Center, West China Hospital, Sichuan University, No. 88, Keyuan South Road, Hi-tech Zone, Chengdu, 610041, China. jqcheng@scu.edu.cn.
  • Hao Yang
    College of Agricultural Science and Engineering, Hohai University, Nanjing 210098, China.

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