DeepGene: an advanced cancer type classifier based on deep learning and somatic point mutations.

Journal: BMC bioinformatics
Published Date: Dec 23, 2016

Abstract

BACKGROUND: With the developments of DNA sequencing technology, large amounts of sequencing data have become available in recent years and provide unprecedented opportunities for advanced association studies between somatic point mutations and cancer types/subtypes, which may contribute to more accurate somatic point mutation based cancer classification (SMCC). However in existing SMCC methods, issues like high data sparsity, small volume of sample size, and the application of simple linear classifiers, are major obstacles in improving the classification performance.

Authors

  • Yuchen Yuan
    School of Information Technologies, The University of Sydney, Darlington, NSW, 2008, Australia.
  • Yi Shi
    College of Food Science and Engineering, Nanjing University of Finance and Economics/Collaborative Innovation Center for Modern Grain Circulation and Safety, Nanjing 210023, People's Republic of China.
  • Changyang Li
    School of Information Technologies, University of Sydney, Australia; Institute of Biomedical Engineering and Technology, University of Sydney, Australia. Electronic address: changyang.li@sydney.edu.au.
  • Jinman Kim
    School of Information Technologies, University of Sydney, Australia; Institute of Biomedical Engineering and Technology, University of Sydney, Australia. Electronic address: jinman.kim@sydney.edu.au.
  • Weidong Cai
    School of Computer Science, The University of Sydney, Darlington, WA, Australia.
  • Zeguang Han
    Key Laboratory of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiaotong University, Shanghai, 200240, China.
  • David Dagan Feng

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