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# <img src="https://gitlab.tudelft.nl/aj-lab/teaching/raw/master/binder/images/logo.jpg" width="250"> Teaching environment of the [AJ lab](http://cryoem.tudelft.nl) at [TU Delft](http://tudelft.nl)
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## High-Resolution Imaging (NB4020)
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### Introduction
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This is the starting page for the cryo-EM Image Processing Practicals of the course High-Resolution Imaging.
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### Practical 1 – Fundamentals of Image Processing
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Launch the virtual learning environment by clicking on the button below.
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[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/git/https%3A%2F%2Fgitlab.tudelft.nl%2Faj-lab%2Fteaching.git/master)
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Navigate to the `binder` folder and then start the file __`nb4020_practial01.ipynb`__ by clicking on it.
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This should open a Jupyter notebook containing your practical assignment.
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The Jupyter Notebook contains code fields such as the one below:
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<img src="https://gitlab.tudelft.nl/aj-lab/teaching/raw/master/binder/images/manual.jpg" width="800;">
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In order to execute these code fields you need to click on the field (which becomes highlighted as above). The order is important, so please work your way through the notebook from the beginning to the end. Also do read the accompanying text - it will explain everything necessary for you to succesfully work through the assignment
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### You can find the solutions to this practical in the solutions folder when launching binder.
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### Practical 2 – 3D reconstruction of human Apoferritin using cryoSPARC
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__In this is practical assignment you will learn:__
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* What the basic steps of a 3D reconstruction workflow using cryo-EM data entail.
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* How to generate 2D class averages from extracted raw particles.
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* How to analyse the quality of 2D and 3D classifications.
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* How to visualise the results from a 3D reconstruction using molecular graphics software.
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#### References
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This interactive practical uses the following dependencies:
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* [numpy](https://www.numpy.org/)
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* [nglview](http://nglviewer.org/nglview/latest/)
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* [mdanalysis](https://www.mdanalysis.org/)
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* [matplotlib](https://matplotlib.org/)
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The material on this page is distributed as Open Educational Resource (OER) under a [CC-BY-NC-SA](http://creativecommons.org/licenses/by-nc-sa/4.0/) licence.
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You may freely copy, reuse, adapt and distribute the material in any form compliant with this licence.
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<small>© Copyright 2019, Arjen J. Jakobi <a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/"><b>CC-BY-NC-SA</b></a></small> |
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