Skip to main content

membrane protein localization for cryo-ET

Project description

Membrain-Pick

Overview

Membrain-Pick is part of the MemBrain suite of tools for processing membranes in cryo-electron tomography. MemBrain-pick's main purpose is to localize membrane-associated particles in the tomograms. To this end, MemBrain-picks takes as input already existing membrane segmentations and processes these to limit the search space for membrane-associated particles. The output of MemBrain-pick is a set of coordinates that can be used for further analysis.

Workflow

The workflow of MemBrain-pick is as follows:

  1. Input: Membrane segmentations in the form of a binary mask (.mrc). Ideally, these segmentations should depict single membrane instances.
  2. Mesh Generation: The membrane segmentations are converted into a mesh representation. At this stage, also tomogram densities are projected onto the membrane mesh.
  3. Ground Truth Generation: The membrane mesh can be loaded into surforama to manually annotate membrane-associated particles. These annotations can then be used to train a MemBrain-pick model.
  4. Training: The generated meshes, along with the annotations, are used to train a model that can predict the location of membrane-associated particles.
  5. Prediction: The trained model is used to predict the location of membrane-associated particles in the membrane segmentations.

Example notebook

For a quick start, you can walk through our example notebook. You can easily run it on Google Colab by clicking on the badge below:

Open In Colab

Key Functionalities

  • Mesh Conversion: Transform membrane segmentations into a mesh representation that can easily be processed by MemBrain-pick and surforama.
  • Model training: Train a model to predict the location of membrane-associated particles.
  • Prediction: Use the trained model to predict the location of membrane-associated particles in membrane segmentations.
  • Initial orientaton assignment: Given a set of positions, MemBrain-pick can assign initial orientations to the particles by aligning them with the membrane normal. -- integration with surforama: MemBrain-pick can be used in conjunction with surforama to manually annotate membrane-associated particles.

Jump to

MemBrain-pick is part of the MemBrain v2 [1] package and still under early development. If you have any questions or suggestions, please contact us at lorenz.lamm@helmholtz-munich.de

[1] Lamm, L., Zufferey, S., Righetto, R.D., Wietrzynski, W., Yamauchi, K.A., Burt, A., Liu, Y., Zhang, H., Martinez-Sanchez, A., Ziegler, S., Isensee, F., Schnabel, J.A., Engel, B.D., and Peng, T, 2024. MemBrain v2: an end-to-end tool for the analysis of membranes in cryo-electron tomography. bioRxiv, https://doi.org/10.1101/2024.01.05.574336

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

membrain_pick-0.0.8.tar.gz (77.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

membrain_pick-0.0.8-py3-none-any.whl (85.3 kB view details)

Uploaded Python 3

File details

Details for the file membrain_pick-0.0.8.tar.gz.

File metadata

  • Download URL: membrain_pick-0.0.8.tar.gz
  • Upload date:
  • Size: 77.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.19

File hashes

Hashes for membrain_pick-0.0.8.tar.gz
Algorithm Hash digest
SHA256 28ff018a977dcefcf7b751458a13cf94ce3aa52604139d8a0c3d1d4684fda251
MD5 7fc847bde660f369e9c23259ca8ee325
BLAKE2b-256 49b85a96c67cbaa8b21ac23f1f42b9d7f9030c6c213a7c130ddd7e68080d6da8

See more details on using hashes here.

File details

Details for the file membrain_pick-0.0.8-py3-none-any.whl.

File metadata

  • Download URL: membrain_pick-0.0.8-py3-none-any.whl
  • Upload date:
  • Size: 85.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.19

File hashes

Hashes for membrain_pick-0.0.8-py3-none-any.whl
Algorithm Hash digest
SHA256 60855e955967ac567cc6092d51e55ccd2f5a0190195c54c4db55462260eba1ae
MD5 3828e66b5f688a6cd859ba1a4a1404b2
BLAKE2b-256 f10f5a975c90a142f4c09b0b2e7510b6a44074ee0a62d476e84adc2f48eb99d3

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page