Identification of Anti-cancer Peptides Based on Multi-classifier System.

Journal: Combinatorial chemistry & high throughput screening
Published Date: Jan 1, 2019

Abstract

AIMS AND OBJECTIVE: Cancer is one of the deadliest diseases, taking the lives of millions every year. Traditional methods of treating cancer are expensive and toxic to normal cells. Fortunately, anti-cancer peptides (ACPs) can eliminate this side effect. However, the identification and development of new anti-cancer peptides through experiments take a lot of time and money, therefore, it is necessary to develop a fast and accurate calculation model to identify the anti-cancer peptide. Machine learning algorithms are a good choice.

Authors

  • Wanben Zhong
    School of Computer Science and Technology, Huaqiao University, Xiamen, Fujian, 361021, China.
  • Bineng Zhong
    Department of Computer Science and Engineering, Huaqiao University, Xiamen, China.
  • Hongbo Zhang
    Department of Computer Science and Engineering, Huaqiao University, Xiamen, China.
  • Ziyi Chen
    Department of Neurology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, Guangdong Province, China.
  • Yan Chen
    Department of Respiratory and Critical Care Medicine, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.

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