autolamella
Science Score: 57.0%
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○Scientific vocabulary similarity
Low similarity (9.6%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: fibsem-os
- License: mit
- Language: Python
- Default Branch: main
- Size: 39.5 MB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 1
- Releases: 0
Metadata Files
README.md
Overview
AutoLamella is a python package for automated cryo-lamella preparation with focused ion beam milling. It is based on openFIBSEM, and currently supports the TESCAN Automation SDK and ThermoFisher AutoScript. Support for other FIBSEM systems is planned.
Documentation
Install
Recommended Installation Guide
Create a new virtual environment from the Anaconda Prompt terminal:
bash
conda create -n fibsem python=3.9 pip
conda activate fibsem
pip install autolamella
Running Autolammela
Open the Anaconda Prompt terminal and run the following commands.
``` bash conda activate fibsem autolamella_ui
```
To launch liftout related methods:
```bash conda activate fibsem autoliftout_ui
```
Citation
If you find this useful, please cite our work.
Genevieve Buckley, Gediminas Gervinskas, Cyntia Taveneau, Hariprasad Venugopal, James C. Whisstock, Alex de Marco, Automated cryo-lamella preparation for high-throughput in-situ structural biology, Journal of Structural Biology, Volume 210, Issue 2, 2020 https://doi.org/10.1016/j.jsb.2020.107488.
See CITATION for more details.
Owner
- Name: FIBSEM Operating System
- Login: fibsem-os
- Kind: organization
- Location: Australia
- Repositories: 1
- Profile: https://github.com/fibsem-os
FIBSEM Operating System
Citation (CITATION.md)
# Citation
If you find this useful, please cite our work.
Genevieve Buckley, Gediminas Gervinskas, Cyntia Taveneau, Hariprasad Venugopal, James C. Whisstock, Alex de Marco,
**Automated cryo-lamella preparation for high-throughput in-situ structural biology**,
*Journal of Structural Biology*,
Volume 210, Issue 2,
2020
https://doi.org/10.1016/j.jsb.2020.107488.
BibTex:
```
@article{BUCKLEY2020107488,
title = "Automated cryo-lamella preparation for high-throughput in-situ structural biology",
journal = "Journal of Structural Biology",
volume = "210",
number = "2",
pages = "107488",
year = "2020",
issn = "1047-8477",
doi = "https://doi.org/10.1016/j.jsb.2020.107488",
url = "http://www.sciencedirect.com/science/article/pii/S104784772030054X",
author = "Genevieve Buckley and Gediminas Gervinskas and Cyntia Taveneau and Hariprasad Venugopal and James C. Whisstock and Alex {de Marco}",
keywords = "Cryo-FIB, Cryo-lamella, Automation, cryo-EM, In situ structural biology",
abstract = "Cryo-transmission electron tomography (cryo-ET) in association with cryo-focused ion beam (cryo-FIB) milling enables structural biology studies to be performed directly within the cellular environment. Cryo-preserved cells are milled and a lamella with a typical thickness of 200–300 nm provides an electron transparent window suitable for cryo-ET imaging. Cryo-FIB milling is an effective method, but it is a tedious and time-consuming process, which typically results in ~10 lamellae per day. Here, we introduce an automated method to reproducibly prepare cryo-lamellae on a grid and reduce the amount of human supervision. We tested the routine on cryo-preserved Saccharomyces cerevisiae, mammalian 293 T cells, and lysozyme protein crystals. Here we demonstrate that our method allows an increased throughput, achieving a rate of 5 lamellae/hour without the need to supervise the FIB milling. We demonstrate that the quality of the lamellae is consistent throughout the preparation and their compatibility with cryo-ET analyses."
}
```
You can download a PDF of our published work at: https://doi.org/10.1016/j.jsb.2020.107488
There is also a bioRxiv preprint of this work available at: https://doi.org/10.1101/797506
GitHub Events
Total
- Delete event: 1
- Push event: 8
- Pull request review comment event: 1
- Pull request review event: 3
- Pull request event: 6
- Create event: 4
Last Year
- Delete event: 1
- Push event: 8
- Pull request review comment event: 1
- Pull request review event: 3
- Pull request event: 6
- Create event: 4
Dependencies
- actions/cache v2 composite
- actions/checkout v3 composite
- actions/setup-python v4 composite
- fibsem >=0.4.0