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  • Description

    a pipeline for the automated detection of membrane-bound proteins in cryo-electron tomograms. It utilizes the geometry of a pre-segmented membrane to reduce the complexity of the detection task. As a result, MemBrain only requires a small amount of annotated data (even one single annotated membrane can be enough!) and can generalize well to unseen tomograms and membranes.

  • Usage

    To list all executables provided by MemBrain, run: $ sbgrid-list membrain Copy to clipboard
  • Usage Notes

    A copy of config.py should be added to the working directory and modified there. Any Membrain scripts being callled should be called from the directory containing the modified config.py file.

    Where the instructions say to call python SCRIPT the python can be removed e.sg. in place of python step1_sample_points.py it should be run as step1_sample_points.py

  • Installation

    Use the following command to install this title with the CLI client: $ sbgrid-cli install membrain Copy to clipboard Available operating systems: Linux 64, OS X INTEL
  • Primary Citation*

    L. Lamm, R. D. Righetto, W. Wietrzynski, M. Pöge, A. Martinez-Sanchez, T. Peng, and B. D. Engel. 2022. MemBrain: A deep learning-aided pipeline for detection of membrane proteins in Cryo-electron tomograms. Computer Methods and Programs in Biomedicine. 224: 106990.

    • *Full citation information available through

  • Keywords

    Electron Microscopy, Tomography

  • Default Versions

    Linux 64:  767b477 (6.1 GB)
    OS X INTEL:  767b477 (2.4 GB)

  • Developers

    Lorenz Lamm, Benjamin D Engel