Multi-labelled proteins recognition for high-throughput microscopy images using deep convolutional neural networks.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: Proteins are of extremely vital importance in the human body, and no movement or activity can be performed without proteins. Currently, microscopy imaging technologies developed rapidly are employed to observe proteins in various cells and tissues. In addition, due to the complex and crowded cellular environments as well as various types and sizes of proteins, a considerable number of protein images are generated every day and cannot be classified manually. Therefore, an automatic and accurate method should be designed to properly solve and analyse protein images with mixed patterns.

Authors

  • Enze Zhang
    High Performance Computer Research Center, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
  • Boheng Zhang
    Department of Automation, Tsinghua University, Beijing, China.
  • Shaohan Hu
    School of Software, Tsinghua University, Beijing, China.
  • Fa Zhang
    High Performance Computer Research Center, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
  • Zhiyong Liu
    State Key Laboratory of Respiratory Disease , Guangzhou Institutes of Biomedicine and Health (GIBH) , Chinese Academy of Sciences (CAS) , Guangzhou-510530 , China . Email: zhang_tianyu@gibh.ac.cn ; ; Tel: (+86)20 3201 5270.
  • Xiaohua Wan
    High Performance Computer Research Center, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China. wanxiaohua@ict.ac.cn.