Identifying Cancer Targets Based on Machine Learning Methods via Chou's 5-steps Rule and General Pseudo Components.

Journal: Current topics in medicinal chemistry
Published Date: Jan 1, 2019

Abstract

In recent years, the successful implementation of human genome project has made people realize that genetic, environmental and lifestyle factors should be combined together to study cancer due to the complexity and various forms of the disease. The increasing availability and growth rate of 'big data' derived from various omics, opens a new window for study and therapy of cancer. In this paper, we will introduce the application of machine learning methods in handling cancer big data including the use of artificial neural networks, support vector machines, ensemble learning and naïve Bayes classifiers.

Authors

  • Ruirui Liang
    School of Life Sciences, Shanghai University, Shanghai, 200444, China.
  • Jiayang Xie
    School of Life Sciences, Shanghai University, Shanghai, 200444, China.
  • Chi Zhang
    Department of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Mengying Zhang
    College of Life Science, Shanghai University, 99 Shang-Da Road, Shanghai 200444, China.
  • Hai Huang
    Institute of Systems Genetics, Department of Critical Care Medicine, Frontiers Science Center for Disease-related Molecular Network, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu 610000, China.
  • Haizhong Huo
    Department of General Surgery, Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China.
  • Xin Cao
    Zhongshan Hospital, Institute of Clinical Science, Shanghai Medical College, Fudan University, Shanghai 200032, China.
  • Bing Niu
    College of Life Science, Shanghai University, 99 Shang-Da Road, Shanghai 200444, China.

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