Using DeepContact with Amira graphical user interface.

Journal: STAR protocols
PMID: 37717213

Abstract

DeepContact is a deep learning software for high-throughput quantification of membrane contact site (MCS) in 2D electron microscopy images. This protocol will guide users through incorporating available DeepContact models in Amira's artificial intelligence module, thereby allowing invoking of DeepContact functions in organelle segmentation and quantifying of MCS with a user-friendly graphical user interface of Amira software. For complete details on the use and execution of this protocol, please refer to Liu et al. (2022)..

Authors

  • Liqing Liu
    National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.
  • Hongjun Wu
    School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China.
  • Shuxin Yang
    Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
  • Ke Yi
    School of Information Engineering, East China Jiaotong University, 330013 Nanchang, Jiangxi, China.
  • Junjie Hu
    Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing 100069, PR China.
  • Li Xiao
    Key Laboratory of Intelligent Information Processing, Advanced Computer Research Center, State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China.
  • Tao Xu
    Department of Urology, Peking University People's Hospital, Beijing, China.

Keywords

External Resources

Popular Topics
Recent Journals