Improve hot region prediction by analyzing different machine learning algorithms.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: In the process of designing drugs and proteins, it is crucial to recognize hot regions in protein-protein interactions. Each hot region of protein-protein interaction is composed of at least three hot spots, which play an important role in binding. However, it takes time and labor force to identify hot spots through biological experiments. If predictive models based on machine learning methods can be trained, the drug design process can be effectively accelerated.

Authors

  • Jing Hu
    College of Chemistry, Sichuan University Chengdu 610064 People's Republic of China xmpuscu@scu.edu.cn +86 028 8541 2290.
  • Longwei Zhou
    School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, Hubei, China.
  • Bo Li
    Electric Power Research Institute, Yunnan Power Grid Co., Ltd., Kunming, Yunnan, China.
  • Xiaolong Zhang
  • Nansheng Chen
    Molecular Biology and Biochemistry, Simon Fraser University, Vancouver, BC, Canada. chenn@sfu.ca.